We take a look at how this 100-year-old technique is shedding new light on protein-protein interactions.

Future Drug DiscoveryVol. 3, No. 1 ForewordOpen AccessWelcome to Volume 3 of Future Drug DiscoveryFrancesca LakeFrancesca Lake *Author for correspondence: E-mail Address: f.lake@future-science.comhttps://orcid.org/0000-0002-7844-6518Newlands Press Ltd, London, N3 1QB, UK Published Online:10 Dec 2020https://doi.org/10.4155/fdd-2020-0033AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinkedInReddit Happy New Year and welcome to Volume 3 of Future Drug Discovery. Despite what has been an unusual year, with the COVID-19 pandemic changing many things in everyday life, 2020 has been an exciting year for the journal. With the eyes of the world on drug development and vaccine discovery, we have been able to provide some great content to increase knowledge of COVID-19 and in some small way contribute to the hunt for novel therapeutics. Of course, exciting developments have been made outside the field of COVID-19 research, and with our first full volume completed we have been able to highlight many different areas from the field of drug discovery, including (but not limited to) immuno-oncology, drug repurposing, antimicrobial resistance and computer-aided drug design. In this Foreword, I will look back and discuss some of the previous year's content highlights, as well as look forward to what is coming in 2021.Content highlights from 2020With the world's attention focused on it, it is unsurprising that our most-read article of 2020, as well as our most-cited article, is about COVID-19. In his Editorial, Suranga L Senanayake discusses drug repurposing strategies for the, at time of his writing, newly declared pandemic [1]. The article has since been downloaded over 10,000 times and has received 24 citations.Senanayake's Editorial was part of our drug repurposing themed issue last April. Each of our four issues in Volume 2 had a theme and, as well as general content, published content specific to the chosen theme. In addition, our Early Career Panel members contributed to a Journal Watch feature for each issue, discussing key papers that had been recently published on the issue's themed topic. So far, our Panel has covered drug repurposing [2], antimicrobial resistance [3] and computer-aided drug design [4]. The theme of this issue is COVID-19 and our panelists were presented with the challenge of selecting key articles from the plethora of papers on SARS-CoV-2 and the disease it causes. Be sure to check it out and see which articles they chose.Our second most-read article of 2020 comes from a group at Charles River Laboratories (MA, USA). In their Special Report, the group, led by Shilina Roman, highlighted the ways in which immune-oncology has progressed over the last 30 years, with a focus on immune checkpoint inhibition, cancer vaccines and T-cell therapies [5]. Another Special Report worth noting was written by a collaborating group from Optibrium Ltd and Intellegens Ltd (both Cambridge, UK) that described the applications of machine learning in the drug discovery process [6]. The authors summarize three recent imputation strategies and compare these with quantitative structure–activity relationship methods.The final article that I will draw your attention to is an Original Research Article that discusses the safety advantages of photocontrol in photopharmacology [7]. Led by senior author Igor V Komarov (Enamine Ltd, Kiev, Ukraine), the researchers aimed to confirm whether photocontrol could increase the safety of a peptide chemotherapeutic agent. The results were promising, justifying the use of peptidic photoswitchable compounds, and the authors encourage further research toward their development.Future Drug Discovery & COVID-19Year 2020 was a tumultuous time for everyone and it involved many cancelled plans and changes to how we work. While we were disappointed to have missed attending conferences and meeting our authors and readers, virtual online events have allowed the drug discovery community to stay as connected as ever and we thank those who have put in the hard work into creating such fabulous meetings. In this issue, check out our interview with the newly elected Chair of ELRIG, Melanie Leveridge, and hear about the challenges of adapting ELRIG Drug Discovery to a digital platform.Back in March, as with the rest of the world, the Future Science Group team transitioned to a working-from-home model and we are proud to have been able to maintain our usual high quality of work outside of our standard office-based setting, with no slowdown in terms of article production or issue compilation.All Future Science Group journals made all their content relevant to coronavirus free to read online (of course, Future Drug Discovery was already open access), and we provided our accelerated publication service free of charge to coronavirus-relevant content to ensure it was posted online as soon as possible. A full list of all coronavirus-related content from across the Future Science Group portfolio can be found on our sister site, BioTechniques [8].As said above, the theme for this issue is COVID-19 so be sure to also check out our Review article that discusses high-throughput approaches of diagnosis and therapies for COVID-19, as well as two Editorials that present the evolution of COVID-19 diagnostics and the challenges to overcome in distributing a vaccine, respectively.Maximizing discovery across the globeFuture Drug Discovery utilizes a number of services to help support its researchers and maximize the visibility and impact of work. These include Publons (rewarding peer review), Altmetrics (tracking online discussion of articles, such as via social media or news outlets), Dimensions (tracking citations) and ScienceOpen (disseminating research widely and putting it into context). Download, Dimensions and Altmetrics statistics are shown on article pages, meaning authors can track the success of their articles.Through our partnership with BioTechniques – a lab methods-focused news and resource site – we are able to provide even more opportunities to increase the visibility of published work. For more information on sharing your research through BioTechniques, please do not hesitate to get in touch.This year, some of the most-viewed BioTechniques content has originated from the field of drug discovery, from regular updates on potential therapies for COVID-19 to a panel discussion: 3D cell cultures, from development to drug discovery [9]. BioTechniques has more exciting drug discovery features in the pipeline for 2021, as well as a dedicated drug discovery section on site and regular technology in drug discovery email updates that can be sent directly to your inbox.Our Editorial Board, Early Career Panel & contributorsWe are hugely thankful to our Editorial Board for their help in creating Future Drug Discovery and their contributions thus far. Our board comprises experts from across the globe crossing both academia and industry. If you would be interested in joining our Editorial Board, please get in touch; we would be delighted to hear your input.At the start of 2020, we also launched our Early Career Panel and they wasted no time in getting stuck in. As said above, the April issue saw the launch of our Early Career Panel Journal Watch – now a regular feature for all our issues. Our panel have also been keen to share their experiences with others just starting out in the field of drug discovery, and in our interview with panelist Sarah Caswell (AstraZeneca, London, UK) you can find some of her top tips for making the choice between a career in academia or industry [10]. A special thanks goes out to each of our panelists for their enthusiasm and support for the journal; we hope to see great things from each of them in their burgeoning careers. If you are in the first 6 years of your career in drug discovery and are interested in joining our panel, please do not hesitate to get in touch.We would also like to thank all the authors and peer reviewers for their contributions in 2020, without whom Volume 2 would not have been possible – we look forward to working with them again in 2021.ConclusionFollowing a successful launch last year and a great second volume, we are excited to see the journal grow and gain recognition in the field over the coming years. Our plans for more themed issues and a focus on early career research mean we have plenty to keep us busy in 2021, although we value any input you may have. If you have any ideas for the journal, be it an outline for an article or a theme for an issue, we would love to hear it, so please get in touch.Financial & competing interests disclosureThe author is an employee of Newlands Press Ltd. The author has no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.No writing assistance was utilized in the production of this manuscript.Open accessThis work is licensed under the Attribution-NonCommercial-NoDerivatives 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/4.0/References1. Senanayake SL. Drug repurposing strategies for COVID-19. Future Drug Discov. 2(2), FDD40 (2020). www.future-science.com/doi/10.4155/fdd-2020-0010Link, Google Scholar2. Miljković F, Xiong R, Sivakumar D, Brown CA. Members of our Early Career Panel highlight key research articles on the theme of drug repurposing. Future Drug Discov. 2(2), FDD39 (2020). www.future-science.com/doi/10.4155/fdd-2020-0009Link, Google Scholar3. Brown CA, Caswell SJ. Members of our Early Career Panel highlight key research articles on the theme of antimicrobial resistance. Future Drug Discov. 2(3), FDD46 (2020). www.future-science.com/doi/10.4155/fdd-2020-0017Link, Google Scholar4. Miljković F, Chaudhari R. Members of our Early Career Panel highlight key research articles on the theme of computer-aided drug discovery. Future Drug Discov. 2(4), FDD52 (2020). www.future-science.com/doi/10.4155/fdd-2020-0026Link, Google Scholar5. Roman S, Holt S, Schueler J. Immuno-oncology: developing integrated approaches towards clinical success of biologics and small-molecule modulators. Future Drug Discov. 2(2), FDD23 (2020). www.future-science.com/doi/10.4155/fdd-2019-0035Link, Google Scholar6. Irwin BWJ, Mahmoud S, Whitehead TM, Conduit GJ, Segall MD. Imputation versus prediction and applications in machine learning for drug discovery. Future Drug Discov. 2(2), FDD38 (2020). www.future-science.com/doi/10.4155/fdd-2020-0008Link, Google Scholar7. Babii O, Afonin S, Schober T et al. Peptide drugs for photopharmacology: how much of a safety advantage can be gained by photocontrol? Future Drug Discov. 2(1), FDD28 (2020). www.future-science.com/doi/10.4155/fdd-2019-0033Link, Google Scholar8. BioTechniques. From the journals: coronavirus (2020). www.biotechniques.com/covid-19/from-the-journals-coronavirus/Google Scholar9. BioTechniques. Panel discussion: 3D cell cultures, from development to drug discovery. (2020). www.biotechniques.com/webinars/sartorius_3d-panel-discussion-3d-cell-cultures-from-development-to-drug-discovery/Google Scholar10. Caswell SJ. Academia vs industry: choosing a career in drug discovery. Future Drug Discov. 2(3), FDD45 (2020). www.future-science.com/doi/10.4155/fdd-2020-0016Link, Google ScholarFiguresReferencesRelatedDetails Vol. 3, No. 1 Follow us on social media for the latest updates Metrics History Received 25 November 2020 Accepted 25 November 2020 Published online 10 December 2020 Published in print March 2021 Information© 2020 Newlands Press LtdFinancial & competing interests disclosureThe author is an employee of Newlands Press Ltd. The author has no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.No writing assistance was utilized in the production of this manuscript.Open accessThis work is licensed under the Attribution-NonCommercial-NoDerivatives 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/4.0/PDF download

Future Science OAVol. 7, No. 1 ForewordOpen AccessWelcome to volume 7 of Future Science OAFrancesca LakeFrancesca Lake *Author for correspondence: E-mail Address: f.lake@future-science.comhttps://orcid.org/0000-0002-7844-6518Future Science Group, Unitec House, 2 Albert Place, London N3 1QB, UKPublished Online:18 Dec 2020https://doi.org/10.2144/fsoa-2020-0180AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinkedInRedditEmail Welcome to volume 7 of Future Science OA. While it has been an unusual year for us all, this Foreword is your usual roundup of the last year of publishing in Future Science OA, as well as a brief look forward to 2021.The year 2020 saw us receive the most submissions ever – at the time of writing in mid-October, we had already received more than throughout the entirety of 2019. This increase in submissions is mirrored by an increase in publications year-on-year, and an increase in citations, to over 1000 thus far in 2020 (Dimensions data). In terms of rankings, our 2019 CiteScore is 3.1, and on track to increase for 2020.Content highlightsIn terms of content highlights, it should be no surprise that our publications related to the COVID-19 pandemic make our most-read list for 2020. These include some thought-provoking editorials, discussing topics such as whether cannabinoids could play a role in quelling the cytokine storm [1], and whether Toll-like receptors could be prime targets to treat the disease [2].It has been noteworthy this year that we have received a large number of submissions related to COVID-19, not all of them good – on average, across our publishing house, we have rejected 50% of these either at the desk, or post-peer review. This was not a trend specific to us – most publishers with relevant journals have seen an influx of COVID-19-relevant submissions, and the race to publish has resulted in many being of insufficient quality and rejected; notably, some have even been published and then retracted once errors have been spotted [3]. I am intrigued to see how lessons learned by both researchers and publishers in this pandemic will affect the scholarly publishing landscape in the future.Other content highlights from this year's Future Science OA include a review of over 600,000 US patients with advanced or metastatic cancer, seeking to estimate the number who are eligible for/could respond to cytotoxic chemotherapy [4]; an analysis of opinions on elective egg freezing across the globe, which resulted in some interesting conclusions and recommendations [5]; and some interesting articles on data and standardization – the proposal of a new, open access natural products database [6] and an introduction to the PRE.M.I.S.E project, which is seeking to standardize data collection following brain radiation therapy [7].This year saw us team up with our sister journal BioTechniques to make the Future Science Future Star Award – recognizing outstanding early career researchers – better than ever. This year saw Andy Tay Kah Ping, a bioengineer from the National University of Singapore, win and we are delighted to have him join us on our early career research advisory panel [8].Finally, this year we also integrated with bioRxiv, meaning authors are now able to submit directly to the journal from that preprint server.Journal statisticsWhile we worked hard to prevent it, the COVID-19 pandemic did affect journal turnaround times this year, although I am pleased that it has been minimized by a commendable home-based effort from our team. On average, we have a desk decision to authors within 2 working days, accepted articles receive that decision 10 weeks after submission, and articles are published 7.5 weeks after acceptance. In 2020 we accepted 66.4% of submissions – down from 80% in 2019, although I note that COVID-19 submissions have been partially responsible for this dip.As mentioned above, we have received over 1000 citations this year, up from the 787 we had received at the time of writing last year's Foreword. This is an appreciable year-on-year increase.Topic areas covered in the journal continue to reflect the state of the biomedical field (Figure 1). Our author demographics remain consistent (Figure 2), and our readership remains global and, again, fairly consistent (Figure 3). These latter two demographics reflect our ability to provide authors from low-income countries with fee waivers, and the fact that we are open access and represented across most scholarly research search engines, ensuring access to as many readers as we can. We also continue to publish lay abstracts, which – we hope – goes some way to ensuring the public can understand the research their taxes may have helped produce.Figure 1. Topics covered in Future Science OA by percentage in 2020.Figure 2. Geographic locations of Future Science OA corresponding authors in 2020.Figure 3. Location of readers of Future Science OA.Thanks to our contributorsAs always, we are hugely thankful to our contributors. In particular this year, a special mention goes to the over 350 researchers who have peer reviewed for us in 2020, despite being locked out of labs or working overtime due to COVID-19.Looking forward to 2021My main hope for 2021 is that the COVID-19 pandemic is consigned to history – not necessarily a given, at this point. In better news, next year we look forward to more special focus issues, the next iteration of the Future Science Future Star Award, and working with more exciting researchers to perfect their publications. We are also currently working to make ourselves compliant with the requirements of Plan S. If you have any suggestions for topic coverage, special issues or collaborations in 2021, please get in touch.Financial & competing interests disclosureF Lake is an employee of Future Science Ltd. The author has no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.No writing assistance was utilized in the production of this manuscript.References1. Onaivi ES, Sharma V. Cannabis for COVID-19: can cannabinoids quell the cytokine storm? Future Sci. OA 6(8), FSO625 (2020).Link, CAS, Google Scholar2. Onofrio L, Caraglia M, Facchini G, Margherita V, De Placido S, Buonerba C. Toll-like receptors and COVID-19: a two-faced story with an exciting ending. Future Sci. OA doi:10.2144/fsoa-2020-0091 (2020) (Epub ahead of print).Link, Google Scholar3. BioTechniques (2020). https://www.biotechniques.com/covid-19/opinion_covid-19-retractions-put-the-spotlight-on-bad-data/Google Scholar4. Maldonado EB, Parsons S, Chen EY, Haslam A, Prasad V. Estimation of US patients with cancer who may respond to cytotoxic chemotherapy. Future Sci. OA 6(8), FSO600 (2020).Link, CAS, Google Scholar5. Nasab S, Ulin L, Nkele C, Shah J, Abdallah ME, Sibai BM. Elective egg freezing: what is the vision of women around the globe? Future Sci. OA 6(5), FSO469 (2020).Link, Google Scholar6. Medina-Franco JL. Towards a unified Latin American Natural Products Database: LANaPD. Future Sci. OA 6(8), FSO468 (2020).Link, Google Scholar7. Chiesa S, Tolu B, Longo S et al. A new standardized data collection system for brain stereotactic external radiotherapy: the PRE.M.I.S.E project. Future Sci. OA 6(7), FSO596 (2020).Link, CAS, Google Scholar8. BioTechniques (2020). https://www.biotechniques.com/general-interest/meet-the-winner-of-the-2020-future-science-future-star-awardGoogle ScholarFiguresReferencesRelatedDetails Vol. 7, No. 1 Follow us on social media for the latest updates Metrics Downloaded 314 times History Received 23 October 2020 Accepted 23 October 2020 Published online 18 December 2020 Published in print January 2021 Information© 2020 Future Science LtdFinancial & competing interests disclosureF Lake is an employee of Future Science Ltd. The author has no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.No writing assistance was utilized in the production of this manuscript.PDF download

BioTechniquesVol. 68, No. 1 ForewordOpen AccessWelcome to BioTechniques 2020!Francesca LakeFrancesca Lake *Author for correspondence: E-mail Address: f.lake@futuremedicine.comhttps://orcid.org/0000-0002-7844-6518Published Online:15 Jan 2020https://doi.org/10.2144/btn-2019-0162AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinkedInReddit This issue marks the first of 2020 and thus a close to 2019. 2019 was (as promised in my introduction to that year's volume!) an exciting year, which saw us continue to push towards reproducibility and launch a new website.2020 promises more of the same – our print editions are being updated to provide you more content and yet use fewer trees (not using magic, I promise you!), and our online content is expanding to bring you more of the methods and protocols you love, as well as more news and expert discussion of matters important to the life science laboratory researcher.This issue contains a look back at 2019 from the Editorial team, as well as a variety of content, including a new open source platform for qPCR data analysis and a look at the latest technological advances in basic research that are pushing us toward the goal of precision medicine.I hope you enjoy this issue, as well as all the issues from the rest of the 68th volume of BioTechniques!FiguresReferencesRelatedDetails Vol. 68, No. 1 Follow us on social media for the latest updates Metrics History Published online 15 January 2020 Published in print January 2020 Information© 2020 Future Science LtdPDF download

Francesca Lake explores the role of antibodies in the ongoing efforts looking to build an atlas of the human body and its diseases.

BioTechniquesVol. 69, No. 3 ForewordOpen AccessKeeping the research spotlight on COVID-19Francesca LakeFrancesca Lake *Author for correspondence: E-mail Address: flake@biotechniques.comhttps://orcid.org/0000-0002-7844-6518Editor in Chief, Future Science Group, Unitec House, 2 Albert Place, London, UKPublished Online:15 Sep 2020https://doi.org/10.2144/btn-2020-0105AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinkedInReddit These past few months, a huge amount of research covering SARS-CoV-2 and COVID-19 has been published, and we commend the extraordinary efforts of the laboratory researchers who have been working hard to combat the virus.While it's an impossible feat to cover all the research that is happening, we have made an attempt on our website – head to www.BioTechniques.com to see our week-by-week coverage. We also had a fascinating Twitter chat where researchers discussed the impact of SARS-CoV-2 and COVID-19 on them – be that impact on their research or themselves, and have covered some interesting insights in the journal – from a new inhaler, to drug discovery and a hugely interesting opinion piece looking at empowering academic labs to test for COVID-19.We're continuing to work hard at ensuring sound research relevant to the pandemic is published as fast as possible, and that publication isn't slowed down for any of our submissions.To all our researcher readers endeavoring to keep the wheels of science moving, keep up the good work – you're amazing!FiguresReferencesRelatedDetails Vol. 69, No. 3 Follow us on social media for the latest updates Metrics History Published online 15 September 2020 Published in print September 2020 Information© 2020 Future Science LtdPDF download

Future Drug DiscoveryVol. 2, No. 1 ForewordOpen AccessWelcome to Volume 2 of Future Drug DiscoveryFrancesca Lake & Jennifer StraitonFrancesca Lake *Author for correspondence: E-mail Address: f.lake@future-science.comhttps://orcid.org/0000-0002-7844-6518Future Science Group, Unitec House, 2 Albert Place, London, N3 1QB, UK & Jennifer StraitonFuture Science Group, Unitec House, 2 Albert Place, London, N3 1QB, UKPublished Online:5 Feb 2020https://doi.org/10.4155/fdd-2019-0036AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinkedInReddit Happy New Year and welcome to Volume 2 of Future Drug Discovery. With 2019 seeing the launch of the journal, it was an exciting year for the Future Drug Discovery team and, in this Foreword, we discuss our highlights and look forward to what is coming in 2020.Content highlights from 2019Future Drug Discovery publishes quarterly issues and many of our issues carry a themed section surrounding a topic of high interest to the drug discovery community. In 2019, we covered the exciting topic of artificial intelligence (AI), which saw us speak with a number of experts to discuss AI concepts, such as the computational chemist, and discuss some of the challenges the AI field faces, including ethics and intellectual property [1]. Separate Editorials also saw R Lawrence (Cancer Research UK Manchester Institute, UK), E Begoli (Oak Ridge National Laboratory, TN, USA) and D Kusnezov (US Department of Energy, DC, USA) discuss their takes on the topic [2,3]. Begoli and Kusnezov summed the topic up nicely in their conclusion: "Clearly the process of drug discovery requires improvements, but the opportunities to do so with AI are manifest." Various commentaries, research, review and opinion pieces were also published. One of our content highlights is a commentary from Zhang et al., which looks at the potential held by metal polyphenol nanonetworks for drug delivery [4]. This article has been read over 900 times and currently holds our most-cited spot. Our most-read article thus far is a research article by Kanna et al., which saw the team investigate whether their perlecan-targeted nanoparticles could improve drug delivery in triple-negative breast cancer [5].We also published a series of interviews with people from various aspects of the drug discovery field discussing life in their areas, including experts from an independent consultancy, contract research organizations and a start-up in a science incubator. We look forward to continuing this series, as it provides an interesting look into the drug discovery careers landscape.Special issues in 2020The year of 2020 will see us publish a plethora of both general and thematic content. This issue is focused around immuno-oncology and we have upcoming issues on drug-repurposing, anti-microbial resistance and computer-aided drug design. If you would like to discuss ideas for any of these issues, please contact us via email.Maximizing discovery across the globeFuture Drug Discovery utilizes a number of services to help support its researchers and maximize the visibility and impact of work. These include Publons (rewarding peer review), Altmetrics (tracking online discussion of articles, such as via social media or news outlets), Dimensions (tracking citations) and ScienceOpen (disseminating research widely and putting it into context). Download, Dimensions and Altmetrics statistics will be shown on article pages, meaning authors can track the success of their articles. At the time of writing (November 2019), our articles had seen nearly 11,000 full-text readers, which is excellent to see. These readers came from across the globe (Figure 1). Figure 1. Future Drug Discovery readership 2019. Expanding the reach of our articlesWe are particularly proud of our partnership with RxNet [6], a free online resource that covers all aspects of pharma R&D. Members of the site gain access to exclusive additional content that builds upon our open access articles, such as our peek behind the paper interview with author J Bajorath. In this interview, he gave further insight into his paper on a novel computational methodology to evaluate chemical optimization [7].Working with the RxNet Editorial team, we were delighted to release the first edition of our Glossary of Drug Discovery last August [8]. Thanks to the help of our expert panel, we compiled a list of all the key terms used in drug discovery – from abbreviated new drug application to Z' factor – and provided handy definitions for your reference. The full glossary is available online and we also hand out physical copies of the book at relevant conferences, so watch out for our booths.In addition, we continue to utilize the power of social media and share all new work on Twitter in order to insure it reaches the largest audience possible; if you do not already, we welcome you to follow us on Twitter (@fsdrugdiscovery).Conferences in 2020Throughout 2019, we were lucky enough to attend multiple exciting conferences, including AAPS PharmSci 360 (TX, USA, 3–6 November 2019), ELRIG Drug Discovery (Liverpool, UK, 5–6 November 2019) and the 4th Medicinal Chemistry and Protein Degradation Summit (London, UK, 28–29 October 2019). It is always great to be able to meet our readers and authors and hear feedback on the journal.If you have any suggestions for conferences in 2020 you would like to meet us at, please let us know. We will be attending various meetings in 2020 with members of the RxNet team, so be sure to look out for our booth and grab a copy of our glossary if you get the chance.Our Editorial Board & contributorsWe are hugely thankful to our Editorial Board [9] for their help in creating Future Drug Discovery and their contributions thus far. Our board comprises experts from across the globe crossing both academia and industry and will be joined in 2020 by a panel of early career researchers who will work to help us ensure the journal is supporting researchers at all career levels. If you would be interested in joining our Early Career Panel, please get in touch; we would be delighted to hear your input.We would also like to thank all the authors and peer reviewers for their contributions in 2019, without whom Volume 1 would not have been possible – we look forward to working with them again in 2020.ConclusionFollowing a successful launch, we are excited to see the journal grow and gain recognition in the field over the coming years. Our plans for themed issues and a focus on early career research mean we have plenty to keep us busy in 2020, although we value any input you may have. If you have any ideas for the journal, be it an outline for an article or a theme for an issue, we would love to hear it, so please get in touch.Financial & competing interests disclosureF Lake and J Straiton are employees of Future Science Ltd. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.No writing assistance was utilized in the production of this manuscript.Open accessThis work is licensed under the Attribution-NonCommercial-NoDerivatives 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/4.0/References1. Future Science. Future Drug Discovery (2019). www.future-science.com/toc/fdd/1/2 Google Scholar2. Begoli E , Kusnezov D . Artificial intelligence's essential role in the process of drug discovery. Future Drug Discov. 1(2), FDD21 (2019). Link, Google Scholar3. Lawrence R . Now the future, we see our dreams: artificial intelligence in drug discovery. Future Drug Discov. 1(2), FDD22 (2019). Link, Google Scholar4. Zhang X , Parekh G , Guo B et al. Polyphenol and self-assembly: metal polyphenol nanonetwork for drug delivery and pharmaceutical applications. Future Drug Discov. 1(1), FDD7 (2019). Link, Google Scholar5. Khanna V , Kalscheuer S , Kirtane A , Zhang W , Panyam J . Perlecan-targeted nanoparticles for drug delivery to triple-negative breast cancer. Future Drug Discov. 1(1), FDD8 (2019). Link, Google Scholar6. RxNet (2020). http://www.rx-network.com Google Scholar7. RxNet. A peek behind the paper: compound optimization monitor (COMO) for computational evaluation of lead optimization (2019). www.rx-network.com/users/242132-future-drug-discovery/posts/54812-a-peek-behind-the-paper-compound-optimization-monitor-como-for-computational-evaluation-of-lead-optimization Google Scholar8. Future Science. RxNet glossary of drug discovery (2019). www.future-science.com/doi/10.4155/fdd-2019-0101s Google Scholar9. Future Science. Future Drug Discovery – editorial advisory board (2019). www.future-science.com/journals/fdd/editors Google ScholarFiguresReferencesRelatedDetails Vol. 2, No. 1 Follow us on social media for the latest updates Metrics History Received 28 November 2019 Accepted 28 November 2019 Published online 5 February 2020 Published in print January 2020 Information© 2020 Future Science LtdFinancial & competing interests disclosureF Lake and J Straiton are employees of Future Science Ltd. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.No writing assistance was utilized in the production of this manuscript.Open accessThis work is licensed under the Attribution-NonCommercial-NoDerivatives 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/4.0/PDF download

Future Science OAVol. 6, No. 1 ForewordOpen AccessWelcome to volume 6 of Future Science OAFrancesca LakeFrancesca Lake *Author for correspondence: E-mail Address: f.lake@future-science.comhttps://orcid.org/0000-0002-7844-6518Future Science Group, Unitec House, 2 Albert Place, London, N3 1QB, UKPublished Online:16 Dec 2019https://doi.org/10.2144/fsoa-2019-0148AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinkedInReddit Welcome to the first issue of volume 6 from Future Science OA! In this Foreword, I will take a look over both the highlights of 2019 in Future Science OA and what we can expect from 2020.The year of 2019 was a fantastic year for the journal, with it becoming indexed on Scopus and seeing an average of 38,000 full-text readers a month across our approximately 450 publications.Those readers come to access great research and we published some really interesting articles in 2019 from a wide range of topics. My personal highlight was an article entitled "'Academic periodization': using approaches from elite sport to benefit early career academics" by J Gonzalez and K Deighton [1]. This article was part of a special issue focused on early career researchers and discussed how periodization – a method used by athletes to maximize performance while minimizing risk of overtraining and injury – can be applied to early career researchers. This article formed part of an excellent issue guest edited by L Heaney (Loughborough University, UK), one of our panel of Young Ambassadors, and is well worth a read for any researcher looking to advance their career without burning out [2].Another fantastic article was a review entitled "Bromodomain and extra-terminal motif inhibitors: a review of preclinical and clinical advances in cancer therapy" by Alqahtani et al [3]. This is our second most-read article from 2019 (after [1]) and makes for a fascinating read.These articles are by no means my only highlights from this year – it is hard to pick from the over 70 new research, review and opinion pieces we have published this year, as well as the novel methodologies and data notes!We also supported the third iteration of the Future Science Early Career Research Award, which has been renamed the Future Science Future Star Award. This year, M Pizarro-Guajardo (Universidad Andrés Bello, Santiago, Chile) won, following stiff competition from 28 candidates [4]. She will be guest editing a special issue of Future Science OA, which will be published in 2020. In the meantime, you can find out more about her fantastic career so far in our winner's podcast [5].This year also saw the publication of a research article from last year's winner, V Mucci [6]. Mucci's study examined the physiological changes that occur during pregnancy for patients with Mal de Debarquement syndrome. We are delighted with how winning the award has increased visibility of research into this rare neurological disorder.Journal statisticsIt currently takes, on average, 9 weeks from submission to acceptance of an article for publication in Future Science OA. The journal currently accepts 80.5% of submissions for publication. At the time of writing (all data were collected on 25 November 2019), the journal has received 787 citations in 2019 – an appreciable increase on 2018 (data taken from Dimensions [7]). This year, Future Science OA articles have also been mentioned in the news 44-times and the editorial team is always delighted to see articles being picked up and communicated to the public.In terms of topic areas, this year the journal has continued last year's trend [8], with a higher percentage of publications in the oncology and immunology/microbiology topic areas (Figure 1). This mirrors the state of the biomedical field, with oncology, immunology and infectious diseases remaining highly researched topic areas. Author demographics also remained fairly consistent, seeing a small decrease in the proportion of authors from the USA, in favor of Africa and Asia, which is something that has been made feasible by our fee waiver program (Figure 2).Figure 1. Topics covered in Future Science OA by percentage in 2019.Figure 2. Future Science OA author demographics in 2019. The proportion of our readers from each continent has also remained relatively similar, with a small decrease in those from the USA and increase in those in Asia (Figure 3). It should be noted, however, that the number of readers is much higher year-on-year.Figure 3. Future Science OA reader demographics in 2019. One final fact I would like to note is that since our launch in 2015, we have had 433 of our articles listed on ScienceOpen [9], which also tells us that those articles have referenced, and thus built upon 15,344 other articles. With reference lists so often hidden behind a paywall, it is fascinating to be able to see such contextual information for our articles.Thanks to our contributorsFuture Science OA would not be able to succeed without the time investment made by our contributors – this includes our excellent editorial board as well as the thousands of authors and peer reviewers we have worked with since our launch in 2015. Looking forward to 2020The year of 2019 has been fabulous and we have some excellent plans for 2020, too. We have recently begun hosting all of our supplementary information on Figshare, meaning that information is both easily available and citable, helping us to support the open data movement. We are also intending to integrate with bioRxiv, allowing those who post their preprints to submit straight to the journal, decreasing the time spent inputting information into submission systems. We will also be supporting the next iteration of the Future Science Future Star Award and publishing the thematic issue guest edited by this year's winner. I look forward to working with you all!Financial & competing interests disclosureF Lake is an employee of Future Science Ltd. The author has no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.No writing assistance was utilized in the production of this manuscript.Open accessThis work is licensed under the Creative Commons Attribution 4.0 License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/References1. Deighton K , Gonzalez JT . 'Academic periodization': using approaches from elite sport to benefit early career academics. Future Sci. OA 5(4), FSO387 (2019). Link, Google Scholar2. Future Science OA . 5(4). https://www.future-science.com/toc/fso/5/4 Google Scholar3. Alqahtani A , Choucair K , Ashraf M et al. Bromodomain and extra-terminal motif inhibitors: a review of preclinical and clinical advances in cancer therapy. Future Sci. OA 5(3), FSO372 (2019). Link, Google Scholar4. The Future Science Future Star Award (2019). https://www.future-science.com/journals/fso/category/earlycareerresearch/award Google Scholar5. Future Science Future Star Award – Winner's Interview (2019). https://www.future-science.com/journals/fso/category/earlycareerresearch/award/winner2019 Google Scholar6. Mucci V , Canceri JM , Jacquemyn Y et al. Pilot study on patients with Mal deDebarquement syndrome during pregnancy. Future Sci. OA 5(4), FSO377 (2019). Link, CAS, Google Scholar7. Dimensions (2019). https://app.dimensions.ai/discover/publication Google Scholar8. Lake F . Welcome to volume 5 of Future Science OA . Future Sci. OA 5(1), FSO358 (2019). Link, Google Scholar9. Scienceopen.com (2019). https://www.scienceopen.com/collection/22fcbb40-bc91-44cf-b677-eeaa8d2e3a7f Google ScholarFiguresReferencesRelatedDetails Vol. 6, No. 1 Follow us on social media for the latest updates Metrics History Published online 16 December 2019 Published in print January 2020 Information© 2019 Newlands PressFinancial & competing interests disclosureF Lake is an employee of Future Science Ltd. The author has no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.No writing assistance was utilized in the production of this manuscript.Open accessThis work is licensed under the Creative Commons Attribution 4.0 License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/PDF download

Rounding up the results from our recent spotlight on CRISPR - are we still just at the beginning for our CRISPR journey?

Future Drug DiscoveryVol. 1, No. 1 ForewordOpen AccessWelcome to the first issue of Future Drug DiscoveryFrancesca LakeFrancesca Lake *Author for correspondence: E-mail Address: f.lake@future-science.comhttp://orcid.org/0000-0002-7844-6518Head of Open Access Publishing, Future Science Group, Unitec House, 2 Albert Place, London N3 1QBPublished Online:2 Jul 2019https://doi.org/10.4155/fdd-2019-0020AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinkedInRedditEmail Hello and welcome to the inaugural issue of Future Drug Discovery, your new peer-review, open-access journal for drug discovery and development research. We are delighted to be joining forces with our international, expert advisory board [1] to launch this new endeavor, which will seek to drive drug discovery research by taking a multidisciplinary and forward-looking stance.Each of our quarterly issues will bring you research and review articles covering the latest advances and hot topics in the field, in addition to opinion and discussion articles covering topics of relevance to the community – all in a free-to-read format.Our first issue begins with an Editorial by Jürgen Bajorath (Rheinische Friedrich-Wilhelms-Universität), aptly discussing the current status of, and future perspectives for, publishing and open access in drug discovery [2]. His article gives a very nice overview of recent trends in the communication of drug discovery research and discusses the increasing importance – yet continuing controversies – surrounding open access and open science in this field. If you are unsure why an open-access drug discovery journal is needed, I recommend reading his article.With Future Drug Discovery, we have created a journal that will allow discussion about the field as a whole, as well as provide a space for publication and discussion of research findings. In addition to research and review articles, we shall be publishing opinion pieces in the form of short editorials (for niche/new topics) and perspectives (for larger topic areas), and short commentaries providing an update on a particular topic. We also have different forms of research articles available – short communications will provide authors the opportunity to publish results that are inconclusive or negative, or to provide updates on previous publications. Methodologies will allow the presentation specifically of a method, and preliminary communications will present early-stage results.Our journal articles will have various metrics available. These will include measures of reads: Altmetrics, which measures the online impact of an article through its mentions on social media and in news outlets; and Dimensions, which track citations. We shall also be partnering with RxNet [12], a community space for discussion of drug R&D, and ScienceOpen [13], a discovery service. This will increase the reach of our articles and also allow readers to delve into reference lists and perform postpublication peer review – I will note here that our articles will be undergoing double-blind prepublication peer review as standard.In addition to the aforementioned article from Bajorath, this first issue includes two articles discussing life in the drug discovery field. The first sees Michael Holzwarth (Actavalon Inc.) comment on the challenges facing biotech start-ups – both for staff and the company as a whole – and how a science incubator can help [3]. The next is an interview with Pauline Lukey, an independent consultant, who discusses moving careers from the pharma industry to consultancy [4].We also cover various disease areas, such as antibiotic resistance, for which combination treatments could be the future [5], and rare diseases, a field for which open science is crucial given the dearth of patient data available to each research group [6].Drug delivery is also a crucial topic area, and in this issue we see experts discussing polyphenols and self-assembly technology [7] and present two research pieces. The first indicates that perlecan-targeted nanoparticles can improve tumor drug delivery for triple-negative breast cancer [8]. The second sought to investigate whether in silico predictions suggesting that nootropic supplements could target the blood–brain barrier translate in vitro, using high-throughput screening [9].We also feature a chromatographic strategy for determination of log P for bRo5 drugs [10], and an expert perspective discussing whether examining chromatographic biomimetic properties at an early stage could reduce later-stage attrition [11].Next issue, we have some exciting articles coming up. We shall be examining the future of artificial intelligence in drug discovery, discussing making a career move to a contract research organization and looking at new advances in therapeutics for migraines and osteoarthritis.We very much hope you enjoy this issue. For anyone looking to ask questions about the journal, discuss a potential submission or join our editorial advisory board, please get in touch with me at f.lake@future-science.com.References1. Future Science. Future Drug Discovery – Editorial Advisory Board. www.future-science.com/journals/fdd/editors Google Scholar2. Bajorath J . Forward-looking perspective on publishing in drug discovery. Future Drug Discov. 1(1), FDD2 (2019). Link, Google Scholar3. Holzwarth M . Benefits of life in a science incubator. Future Drug Discov. 1(1), FDD3 (2019). Link, Google Scholar4. Lukey PT . Independent consultancy in drug discovery and development: a personal perspective. Future Drug Discov. 1(1), FDD4 (2019). Link, Google Scholar5. Coates A . The future of antibiotics lies in combination treatments. Future Drug Discov. 1(1), FDD5 (2019). Link, Google Scholar6. Naegeli K , Havener T , Aw WY , Morris D . An open science rare diseases research initiative: the University of North Carolina Catalyst. Future Drug Discov. 1(1), FDD6 (2019). Link, Google Scholar7. Zhang X , Parekh G , Guo B et al. Polyphenol and self-assembly: metal polyphenol nanonetwork for drug delivery and pharmaceutical applications. Future Drug Discov. 1(1), FDD7 (2019). Link, Google Scholar8. Khanna V , Kalscheuer S , Kirtane A , Zhang Q , Panyam J . Perlecan targeted nanoparticles for drug delivery to triple negative breast cancer. Future Drug Discov. 1(1), FDD8 (2019). Link, Google Scholar9. Alsarrani A , Kaplita PV . In silico and in vitro evaluation of brain penetration properties of selected nootropic agents . Future Drug Discov. 1(1), FDD9 (2019). Link, Google Scholar10. Ermondi G , Vallaro M , Goetz G , Shalaeva M , Caron G . Experimental lipophilicity for beyond rule of 5 compounds. Future Drug Discov. 1(1), FDD10 (2019). Link, Google Scholar11. Valko KL . Application of biomimetic HPLC to estimate in vivo behavior of early drug discovery compounds. Future Drug Discov. 1(1), FDD7 (2019). Link, Google Scholar12. RX Network. www.rx-network.com/ Google Scholar13. Science Open. www.scienceopen.com/ Google ScholarFiguresReferencesRelatedDetailsCited ByMXene Composite Nanofibers for Cell Culture and Tissue Engineering23 March 2020 | ACS Applied Bio Materials, Vol. 3, No. 4 Vol. 1, No. 1 Follow us on social media for the latest updates Metrics Downloaded 780 times History Received 28 May 2019 Accepted 30 May 2019 Published online 2 July 2019 Published in print July 2019 Information© 2019 Newlands Press LtdPDF download

BioTechniquesVol. 66, No. 5 From the EditorOpen AccessAI in the life sciences: on the up, or over-hyped?Francesca LakeFrancesca Lake*Author for correspondence: E-mail Address: f.lake@future-science-group.comPublished Online:3 May 2019https://doi.org/10.2144/btn-2019-0040AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinkedInReddit Recently I found myself having a fascinating conversation about the potential artificial intelligence (AI) holds for drug discovery. A field that is plagued by high failure rates and thus high costs, AI has the potential to drastically improve the efficiency of the drug discovery process. However, that's not the only field seeing AI's potential.Deep learning has recently been used in engineering, to try to predict material properties without having to physically create the structure. It has been suggested for use in predicting risk of early death in a bid to improve preventative healthcare. It also has shown potential for use in individualizing brain tumor treatment, and in predicting survival for those with ovarian cancer.On the face of it, it sounds like AI will be able to revolutionize most of the fields within the life sciences, and this is already happening in some. However, as we walk further down the AI path, plenty of questions are arising.For example, just how much can a machine learn – a tool might be successful in the short term, but how can we tell if it continues to be so? How will its use affect intellectual property? Given that data will be core to many AI-based processes, how will it affect data privacy, as well as value? And how will it impact the employment landscape?These questions will certainly need to be considered carefully if AI's star continues to rise, and I'm inclined to think it does indeed have a bright future in the life sciences. However, it also has the potential to fall foul of its own fame, something that has affected concepts such as CRISPR and organs-on-chip, where hype has outshone the results.Regardless of the questions, it seems that AI is here to stay, and I'm looking forward to seeing how scientists continue to harness it in ever new ways, albeit while trying not to think too hard about the inevitable plot lines of most AI-related films…FiguresReferencesRelatedDetailsCited ByEthics in the Era of Artificial IntelligenceIEEE Pulse, Vol. 11, No. 3 Vol. 66, No. 5 Follow us on social media for the latest updates Metrics History Published online 3 May 2019 Published in print May 2019 Information© 2019 Future Science LtdPDF download

BioTechniquesVol. 67, No. 4 From the EditorOpen AccessIs ethics failing to keep up with scientific advances?Francesca LakeFrancesca Lake*Author for correspondence: E-mail Address: f.lake@future-science.comEditor in Chief, Future Science Group, Unitec House, 2 Albert Place, London, UKPublished Online:17 Sep 2019https://doi.org/10.2144/btn-2019-0108AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinkedInReddit Our recent Spotlight on CRISPR, along with our news coverage of the creation of the first human–monkey chimera, raised interesting ethical questions. How long should a CRISPR-edited embryo be allowed to develop for? What about a chimera? Is editing 'normal' traits acceptable? These are all questions that have been raised and – according to our survey at least – remain unanswered, which suggests that our continuing advances in scientific abilities is outpacing what we feel comfortable with morally.With ethical issues also being raised by advances in AI, data analytics and synthetic biology, its clear that our increasing technical abilities need to come hand-in-hand with increased ethical oversight. This is happening to an extent – new ethics bodies are cropping up; for example, China has recently announced a plan to establish a national science and technology ethics committee, and the WHO has announced an advisory committee to develop global standards for genome editing.However, these two committees at least feel somewhat like reactions to questionable research already performed – is there a way to proactively prevent research overstepping the ethical mark in the future without having a negative effect on advancement? Would something akin to the Hippocratic Oath – currently taken by physicians to ensure ethical practices – work if applied to those in the life sciences? Food for thought.FiguresReferencesRelatedDetailsCited ByChimeric Humanized Vasculature and Blood: The Intersection of Science and EthicsStem Cell Reports, Vol. 14, No. 4 Vol. 67, No. 4 Follow us on social media for the latest updates Metrics History Published online 17 September 2019 Published in print October 2019 Information© 2019 Future Science LtdPDF download

Welcome to the first issue of volume 5 from Future Science OA! We are delighted to be celebrating our fifth birthday this year, which will also see us surpass 400 publications. In this Foreword, I will take a look back over our highlights from 2018, and look forward to what we have planned in 2019. 2018 has seen us continue to disseminate our content in the traditional ways, as well as the novel. We now see 6% of our readers come through social media, which is a threefold increase on 2017. Furthermore, 2018 saw us partner with ScienceOpen, the research and publishing network. All Future Science OA content is now available in a ScienceOpen collection [1]. Here, you can find all of our articles and view some of their metrics. One of our favorite parts of ScienceOpen is the ability to view the reference list of each article in detail, meaning it is easy to find the most relevant, related content to continue your research. We also supported the second iteration of the Future Science Early Career Research Award [2]. This year saw us receive 19 nominations, from which a shortlist of five finalists was selected by our expert judging panel. The panel this year comprised members of our Editorial Board and Young Ambassador panel, including Joe Abisambra, the winner of the 2017 award. Viviana Mucci was then announced as the winner following a public vote, which saw over 4000 voters choose their winner [3]. We recommend reading her profile as she is doing some fabulous work. With gender equality in the sciences continuing to be an important topic of discussion, we were delighted to see that all five finalists were outstanding female early career researchers – this bodes well for the future. We have also been supporting researchers even earlier in their careers this year. The ChrisXandDrake Science Award is an initiative that promotes science in primary schools [4]. This year, the initiative and a team of researcher mentors took 9to 10-year-old school children through the scientific investigation process, from hypothesisbuilding through study design to data collection, write-up and publication. We were delighted to attend their poster presentation event, and have since published their write-ups in Future Science OA [5]. It was wonderful to see children learning more about the research process, and a delight to hear them talking about their future plans for careers in scientific research.

BioTechniquesVol. 67, No. 5 From the EditorOpen AccessSaving the trees, revitalizing your coffee table and shoring up the futureFrancesca LakeFrancesca Lake*Author for correspondence: E-mail Address: f.lake@future-science.comHead of Open Access Publishing, Future Science Group, Unitec House, 2 Albert Place, London, UKPublished Online:24 Oct 2019https://doi.org/10.2144/btn-2019-0132AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinkedInReddit Many of our readers know BioTechniques from the print edition that finds its way onto the coffee table every month. Lately, many of our readers will also have become aware of how our website has evolved, becoming a place to discover expert commentary and discussion, with thought-provoking Interviews, Opinion pieces, Podcasts and panel discussions examining the latest tools and techniques available to the lab researcher, in addition to our educational webinars and News section.Both our online and print articles are free to read, and it is our intention to keep it that way. However, the publishing landscape is changing, and BioTechniques must, like our labs, continually evolve to keep up. That's why we have some changes coming in 2020.First up, we are revitalizing our print edition. We care about the planet, and thus as of 2020 we will be consolidating our articles into quarterly print editions, helping us reduce our impact on the environment and save trees. This won't mean you lose out – we will be publishing the same (if not more!) content, but it will arrive on your coffee table with a refreshed feel – Reports and Benchmarks will remain alongside exciting editorial content such as our traditional Tech News, Interviews, Top Tips and other fascinating articles.Second up, the way you use the website is changing. Going forward, readers will be able to access three articles a month before they are required to log-in with their (free) subscription – and I emphasize that that subscription will be free. Our peer-reviewed articles will remain open access, as they always have been.In the rapidly changing landscape of scientific research and publishing, these changes will shore up the future for BioTechniques, allowing us to maintain our editorial excellence and continue to provide you, our reader, with free-to-access content. By continuing your subscription, you will help us continue to provide the latest in methods, tools and technical advances freely to researchers across the globe, regardless of where they are.So please, continue to read and enjoy BioTechniques for free, for years to come, and email me if you have any queries regarding the above at flake@biotechniques.com.FiguresReferencesRelatedDetails Vol. 67, No. 5 Follow us on social media for the latest updates Metrics History Published online 24 October 2019 Published in print November 2019 Information© 2019 Future Science LtdPDF download

Francesca Lake explores the latest goings on in techniques advancing precision medicine

A collection of protocols from BioTechniques

Future Drug DiscoveryVol. 1, No. 2 EditorialOpen AccessArtificial intelligence in drug discovery: what is new, and what is next?Francesca LakeFrancesca Lake *Author for correspondence: E-mail Address: f.lake@future-science.comhttps://orcid.org/0000-0002-7844-6518Newlands Press, Unitec House, 2 Albert Place, London, UKPublished Online:14 Oct 2019https://doi.org/10.4155/fdd-2019-0025AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinkedInRedditEmail Keywords: artificial intelligencedrug discoverydrug designcomputational chemistryArtificial intelligence (AI) – that is, machine intelligence – has the potential to make waves in drug discovery. However, it is not without its challenges. In this issue of Future Drug Discovery we focus on AI for drug discovery purposes, and in this editorial we take a look at how AI is being utilized throughout the drug design and development processes, and the positives and negatives posed by the technology.Designing a computational computer chemistBeginning with the earliest stages of drug discovery, AI has been harnessed to develop completely new lead compounds that exhibit desired activity in silico [1]. Combining computational de novo design with AI could allow a 'computer chemist' to learn from known useful compounds and enable the production of chemically correct and synthesizable structures with a planned biological activity. Until a study by Merk et al. at the Swiss Federal Institute of Technology (ETH; Zurich, Switzerland), AI was stymied by the huge number of possibilities involved and the potential for multiple targets [1]."Advanced machine learning requires large well-annotated datasets that need to be compiled or generated," explained Gisbert Schneider, group leader for the study. "Also, the chemical structure of a drug alone rarely accounts for the observed pharmacological effect in a simple fashion. Most drugs have multiple biological targets and activities, and their relative importance is highly dependent on the individual genetic profile of patients, and a range of other factors. In certain areas of drug design we are confronted with inherently ill-posed problems owing to a multitude of often unknown contributing factors" [2].As a result, previous efforts have only been able to use the approach retrospectively; however, Schneider's group was able to apply it prospectively, creating a nonhuman 'drug designer'."Modern machine-learning methods are very fast and can consider several design goals in parallel," he noted. "So, our drug design software was trained to recognize important features and characteristics of known drugs. The obtained models were then used to automatically assemble new molecules with these learned desired properties from scratch" [2].The computer brain versus the human brain for drug designAI is also being harnessed at the lab of Ola Engkvist, section head of the hit discovery department at AstraZeneca's Discovery Sciences Department (Cambridge, UK). In collaboration with the University of Muenster (Germany), his group has been seeking to solve the problem that drug design algorithms are not able to efficiently search the whole chemical space. Their recurrent neural networks (RNNs) are now able to, through learning."RNNs don't really understand chemical structures; they learn rules about how to generate novel character strings that correspond to molecules within the chemical space," he explained. However, this approach still requires human input. "Since humans decide on which chemical space to train the RNN, humans are essential to the process. What the RNN can do is generate many more molecules that are drug-like and can combine these with information about a drug target to home in on a certain part of the drug-like chemical space that the human may not have thought of," he continued [3].Another neural network-based technology is Atomwise (CA, USA). Invented by Abraham Heifets and Izhar Wallach, Atomwise uses the same technology underlying 2D image and speech recognition, applying it to molecular recognition (aka, 3D image recognition). This matchmaker technology uses machine learning to screen compounds quickly; however, again it requires a human counterpart.Heiferts noted: "To support the subtle statistical approaches, you need massive datasets. The last time I checked the NIH's PubChem database, I think there were 240 million chemical compounds in there. But that didn't exist 20–30 years ago. If you have small datasets and powerful statistics, you are going to memorize the dataset and you're not actually going to generalize, so you have to match the power of the algorithm to the size and complexity of the data. Of course, not all data is good data. 98% of those data sets don't pass our quality control filters. The old tenet of garbage in, garbage out holds – if you don't carefully go through your data, you're going to learn artefacts, you're going to fool yourself. That's part of the reason why we have a team of medicinal chemists and structural biologists, as well as machine learning and computer scientists" [4].Harnessing AI for hit identificationOne project in which Atomwise is involved is being led by Grant Wishart, leader of the Charles River Computer-Aided Drug Design & Structural Biology group (Cambridge, UK). The project is allowing Charles River, a contract research organization, to predict protein target binding of huge numbers of compounds, including synthesis on-demand libraries."Access to such large regions of chemical space becomes very important for those protein targets that are traditionally considered as challenging for hit finding and highly competitive 'hot targets' where access to novel chemical space is highly desired," highlighted Wishart [5].However, he also noted that Charles River is in the early stages of applying AI for hit identification, and that it is currently too early to say it has been a success. "However, it is anticipated that the application of AI technologies in our organization will grow significantly in the near future and will have a major positive impact upon our ability to find hits for challenging targets," he continued. "This is expected to result in quicker timelines to transition projects into hit-to-lead and lead optimization phases" [5].Again, the amount of data required for such projects has raised a challenge – both in terms of standardization, and in intellectual property (IP). "As a services company, this data is most often owned by our partners. Therefore, within individual partner drug discovery projects this data is being leveraged to advance the project and at a more holistic level we are working with our partners to seek permission, where appropriate to explore global modelling efforts," Wishart noted [5].Who holds the IP in AI drug discovery?The drug discovery field has always been protective of IP. Given the huge amount of data required for machine learning to be successful, it is unsurprising that issues with IP are even bigger here.Takeshi S Komatani, of the law firm Shusaku Yamamoto (Japan), notes that IP in AI has two main aspects – subjective and objective. The subjective issues center around who the inventor is. "According to the literal interpretation of the Japanese Patent Act, an invention created solely by an AI cannot be protected by the patent act and rather goes to the public domain," he points out. This is more or less the same in the USA. "Any 'inventions' 'invented' by 'AI' would belong to the public domain. However, this needs extensive arguments and needs to be debated in detail from the respective field of professionals and expertise," he continued. For the objective side, the problem lies in what is patentable subject matter. "Practitioners are struggling to prepare a reasonable and robust specification/description to secure patent rights to AI-related technologies. With respect to copyrightable works such as those related to experimental data or the like, things are more complicated. This is because copyright does not require registration. Therefore, no one can actually identify who owns what" [6].Another problem is the data itself. In this vein, the recent G20 summit in Osaka proposed the launch of the 'Osaka track' framework for free cross-border data flow, promoting cross-border data flow with better protection of personal information, IP and cybersecurity [7]. That meeting saw 24 countries sign the statement. It will be interesting to see how this framework affects data IP in AI-related drug discovery.The inevitable question of ethicsIn addition to IP, AI raises various other ethical considerations. For example, patient data are invaluable to drug discovery research, but patient privacy needs to be maintained. While this is legally a requirement in many areas and multiple methods exist to ensure privacy, can it be guaranteed that data are 100% secure? "I don't think data is ever 100% secure," commented John Mitchell (University of St Andrews, UK). "It's well understood that a determined and resourceful adversary might try to reconstruct anonymized data with reference to other available fragments of information. But medical data will be safer than most of the trails of digital footprints we leave in the sand of the internet" [8].He believes using AI for personalized medicine might be a more pressing issue. "AI-driven medicine may well be personalized medicine, and dependent on each individual's genetic code. That means that in order to benefit, our genomes will have to be out there in some sense. If my genome is out there, what if it contains potentially bad news, such as a likelihood of developing a debilitating disease in the future? Perhaps I want to know and want my doctors to know, in order to find the optimal preventative measures and, if necessary, treatments. Maybe I'd rather not know, in order not to waste the present worrying about something that may or may not happen in the future. Should insurers have access to such information? Or what about family members? These questions are likely to become more pressing in the coming years" [8].However, he is concerned that job attrition is the most pressing concern. Even though the Industrial Revolution was overall a good thing, many people suffered from losing their jobs to machines, and AI has the potential to repeat that process. 'The challenge is to manage an inevitable process of change and transformation while minimizing negative consequences for people and their communities. May be AI and robots will make society wealthy enough that we can afford to pay a universal citizen's income at a decent level with extra income available for those who take on paid jobs; this still provides the challenges of distributing work, opportunity and leisure time fairly while giving people something worth living for. It is also possible that we will just create more jobs for humans, probably roles as unimaginable now as a web designer or social media engagement coordinator would have been in the 1960s' [8].Open sourceWhile data privacy and IP are important considerations, some teams are providing machine-learning software open source. One AI effort has seen Anne Carpenter (Broad Institute of Harvard and MIT, MA, USA) creating a code to solve the bottleneck she encountered when processing cell images and making that code open source. 'CellProfiler' automatically identifies cells in images and measures properties. The later 'CellProfile Analyst' uses machine learning to recognize cells with a particular phenotype."This ability to quantitatively match cells based on their image-based profile is deceptively simple but there are so many applications in drug discovery," explained Carpenter. "For example, we can take cells from patients with and without a disease and compare their morphology. If we find a difference in their profiles, this can serve as a diagnostic tool, but even better we can now test thousands of drugs to find any that are able to reverse the disease profile and make cells look healthy again" [9].Other open-source, deep-learning tools have also recently been announced, such as PaccMann, INtERAcT and PIMKL from IBM Research – Zurich (Switzerland) [10]. PaccMann incorporates transcriptomics, cellular protein interactions and compound molecular structure to predict cancer cell drug sensitivity [11]. INtERAcT uses unsupervised machine learning to examine cancer research publications and extract interactions, such as protein–protein interactions. PIMKL is a machine-learning algorithm able to predict phenotype from multiomic data. With these methods only just openly available, it will be interesting to see how they are utilized going forward.So what is next for AI in drug discovery?Clearly, AI is already helping drug discovery – it can help identify drug targets, find good molecules from data libraries, suggest chemical modifications, identify candidates for repurposing and so on. However, in the short term it has a number of challenges to overcome. The buzz around AI could be its own downfall – Mitchell noted: "often new approaches to drug discovery get overhyped, like combinatorial chemistry did a few years ago, and failure to manage unrealistic expectations leads to an inevitable let down and to a perceived bursting of the bubble. It's better to expect incremental advances and perhaps to be pleasantly surprised than to promise a revolution that never materializes" [8]. With that, AI needs to prove itself. Heifets agrees that this is a huge challenge: "It's insufficient to predict yesterday's weather. You have to predict tomorrow's weather, and get it right over and over and over again. I think in this field, whether it is AI or anything else, you have to be able to show a couple dozen successes when nobody knew what the answer was" [4].The availability of robust datasets and the need for investment to access AI technology could also prove to be hurdles.However, there is plenty of excitement over the future; "I think the next 5–10 years will be really exciting," enthused Engkvist. "I think one of the next big advances will be a much tighter integration with automation that allows us to move from an augmented drug design paradigm where the design chemist takes all the decisions to an autonomous drug design paradigm, where the system can autonomously decide which compound to make next" [3]. Schneider agrees autonomy is the next exciting step: "I expect fully autonomous laboratories iterate through the design–make–test–analyze cycle of drug discovery without direct human intervention. The result could be the delivery of better starting points for drug discovery faster" [2].Financial & competing interests disclosureThe authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.No writing assistance was utilized in the production of this manuscript.Open accessThis work is licensed under the Attribution-NonCommercial-NoDerivatives 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/4.0/DisclaimerThis article was written as part of a collaboration with Eureka, the Charles River Labs blog. The interviews included form part of an interview series available on Eureka. The opinions expressed in this Editorial are those of the interviewees and do not necessarily reflect the views of Newlands Press Ltd.References1. Merk D , Friedrich L , Grisoni F , Schneider G . De novo design of bioactive small molecules by artificial intelligence (2018). https://onlinelibrary.wiley.com/doi/full/10.1002/minf.201700153 Google Scholar2. Eureka. A chemistry-savvy AI joins the lab team (2019). https://eureka.criver.com/a-chemistry-savvy-ai-joins-the-lab-team/ Google Scholar3. Eureka. The computer as drug hunter (2019). https://eureka.criver.com/the-computer-as-drug-hunter/ Google Scholar4. Kelder R . Commercializing deep neural networks for drug discovery (2019). https://eureka.criver.com/commercializing-deep-neural-networks-for-drug-discovery/ Google Scholar5. Eureka. The future of drug discovery: AI impacting upon hit ID strategies (2019). https://eureka.criver.com/the-future-of-drug-discovery-ai-impacting-upon-hit-id-strategies/ Google Scholar6. Eureka. For AI-enabled drug discoveries, who owns the science? (2019). https://eureka.criver.com/for-ai-enabled-drug-discoveries-who-owns-the-science/ Google Scholar7. Sugiyama S . Abe heralds launch of 'Osaka Track' framework for free cross-border data flow at G20. The Japan Times, 28th June (2019). https://www.japantimes.co.jp/news/2019/06/28/national/abe-heralds-launch-osaka-track-framework-free-cross-border-data-flow-g20/#.XTXXFuhKijR Google Scholar8. Eureka. Ethical dilemmas that artificial intelligence raise in the lab (2019). https://eureka.criver.com/ethical-dilemmas-that-artificial-intelligence-raise-in-the-lab/ Google Scholar9. Eureka. Image-based cell profiling (2019). https://eureka.criver.com/image-based-cell-profiling/ Google Scholar10. Manica M , Cadow J . Novel AI tools to accelerate cancer research (2019). https://www.ibm.com/blogs/research/2019/07/ai-tools-for-cancer-research/ Google Scholar11. Oskooei A , Born J , Manica M , Subramanian V , Sáez-Rodríguez J , Martínez MR . PaccMann: prediction of anticancer compound sensitivity with multi-modal attention-based neural networks (2019). https://arxiv.org/abs/1811.06802 Google ScholarFiguresReferencesRelatedDetailsCited ByBig Data in Drug Discovery1 January 2022Evolving scenario of big data and Artificial Intelligence (AI) in drug discovery23 June 2021 | Molecular Diversity, Vol. 25, No. 3Prospective Artificial Intelligence to Dissect the Dengue Immune Response and Discover Therapeutics15 June 2021 | Frontiers in Immunology, Vol. 12İLAÇ KEŞFİ VE GELİŞTİRİLMESİNDE YAPAY ZEKÂ11 May 2021 | Ankara Universitesi Eczacilik Fakultesi DergisiDesign and Development of Cholinesterase Dual Inhibitors towards Alzheimer's Disease Treatment: A Focus on Recent Contributions from Computational and Theoretical Perspective27 November 2020 | ChemistrySelect, Vol. 5, No. 44The power of deep learning to ligand-based novel drug discovery31 March 2020 | Expert Opinion on Drug Discovery, Vol. 15, No. 7 Vol. 1, No. 2 Follow us on social media for the latest updates Metrics Downloaded 13,522 times History Received 29 July 2019 Accepted 29 July 2019 Published online 14 October 2019 Published in print October 2019 Information© 2019 Newlands Press LtdKeywordsartificial intelligencedrug discoverydrug designcomputational chemistryFinancial & competing interests disclosureThe authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.No writing assistance was utilized in the production of this manuscript.Open accessThis work is licensed under the Attribution-NonCommercial-NoDerivatives 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/4.0/DisclaimerThis article was written as part of a collaboration with Eureka, the Charles River Labs blog. The interviews included form part of an interview series available on Eureka. The opinions expressed in this Editorial are those of the interviewees and do not necessarily reflect the views of Newlands Press Ltd.PDF download