Growing global concern about climate change, alongside the widespread use of inhaler therapies, has intensified interest in the environmental sustainability of inhalers. The respiratory care community is increasingly focused on how to balance effective disease management with the need to avoid exacerbating environmental determinants of respiratory illness. Since Pharmaceutical Medicine last examined this topic in its article Sustainability in Inhaled Drug Delivery, the field has evolved rapidly, with notable developments. This Leading Article reviews the current evidence on the carbon footprints of inhalers and discusses strategies-along with their implications for patient care-aimed at reducing the environmental impact of inhaler therapies. We focus on strategies at the (a) health system level, including optimisation of respiratory care and inhaler choice, adherence, and technique, and (b) pharmaceutical industry level, including innovation and action related to next-generation lower-carbon propellants such as HFA-152a and inhaler circularity. While sustainability strategies exist, we acknowledge that progress is slow, and highlight key implementation, financial, and regulatory challenges that constrain their uptake. The article concludes by outlining recommendations to help support sustainable and effective respiratory care.
Artificial intelligence (AI) transcription systems using large language models (LLMs) and natural language processing (NLP) may reduce documentation burden. Medical science liaisons (MSLs) face challenges documenting scientific interactions with health care professionals (HCPs). This Amgen study evaluated whether AI-enabled transcription improved MSL documentation experience and insight documentation compared with existing practice (EP) of manual customer relationship management (CRM) entry. This randomized crossover study enrolled 27 MSLs from six Amgen Asia-Pacific affiliates; 78
Clinical trial recruitment continues to fail at scale, with eligible patients often invisible to routine screening despite being present in electronic health records. Disease stage, treatment response, biomarker results, and clinical reasoning are frequently documented in narrative form rather than structured fields, placing eligibility-relevant information beyond the reach of conventional recruitment workflows. This narrative review examines applications of artificial intelligence (AI), and particularly large language models, across the recruitment pipeline. The evidence is organized around two ceilings. The discovery ceiling reflects the limits of identifying eligible candidates in clinical data, and current evidence suggests AI can raise it, improving discovery and screening efficiency in defined workflows. The enrollment ceiling reflects the human, logistical, ethical, and institutional barriers that persist after a patient has been identified. AI can make invisible patients visible, but visibility is not enrollment, and AI alone cannot remove these barriers. Upstream applications in trial design, predictive enrichment, site selection, and patient-facing engagement are also reviewed, together with governance requirements for equity, privacy, regulation, and workflow integration. Current evidence remains concentrated in retrospective evaluations, with limited prospective, multicenter validation and few demonstrated gains in enrollment, representativeness, or cost effectiveness. Recruitment AI is therefore best treated as a governed, human-supervised support tool that is locally validated and evaluated against downstream outcomes such as enrollment, diversity, burden, and cost.
An integrated evidence generation plan (IEGP) can transform the effectiveness of how pharmaceutical companies demonstrate the value of new therapies. Medical Affairs professionals are uniquely positioned to lead and shape an IEGP, leveraging their scientific and clinical expertise, while maintaining a focus on patient access needs among competing cross-functional priorities. In this article, we explore key subfunctions within Medical Affairs, describing their contributions to the development of an IEGP and discussing the impact of the evolving healthcare environment on their responsibilities. Finally, we consider how to measure the impact of an IEGP for pharmaceutical companies and describe what success looks like for Medical Affairs in the development of an IEGP. Our companion article in this issue of Pharmaceutical Medicine provides more details of the process of integrated evidence generation planning and considers the impact of evolving regulatory and health technology assessment landscapes.
Biosimilar medicines have the potential to reduce costs and expand patient access, yet uptake rate remains uneven world-wide. This policy review will (1) evaluate and compare biosimilar medicine uptake and policy frameworks across eight countries in the Organisation for Economic Co-operation and Development (OECD) including Australia and (2) apply Actor Network Theory (ANT) translation to interpret the mechanisms underlying the observed differences in adoption. Targeted searches of academic databases and grey literature were conducted for the period 2017 to 2025. Policies from Australia, Belgium, Denmark, France, Germany, Italy, Canada, and UK were reviewed and classified as either supply-side or demand-side interventions. Maximum market penetration rates of six selected biosimilar products were assessed as the principal indicators of successful adoption. Actor network theory was applied to interpreting how policy makers align other actors in the network to various interventions and to explain differences in effectiveness. Correlation exists between countries achieving high levels of uptake and implementation of two distinct policy uptake methodologies. The first combined multiple supply- and demand-side measures, including incentives, substitution policies, and educational initiatives. The second relied primarily on coordinated national tendering systems operating across hospital and retail markets. Moderate-performing countries employed similar measures but with less consistent implementation, while lower-uptake countries tended to rely predominantly on price controls with limited demand-side engagement. Overall, policy approaches that either integrate multiple complementary interventions or implement robust tendering frameworks appear to be correlated with highest rates of biosimilar uptake. Applying ANT highlights how policy design interacts with healthcare networks, offering insights that may inform more effective biosimilar policy development. Actor network theory illustrates why the policy combinations may be associated with higher levels of uptake: they translate diverse actors into more stable configurations that support adoption. This study examines how countries can increase the use, or “uptake,” of biosimilar medicines, which are lower-cost versions of existing biological drugs that deliver similar safety and effectiveness. The researchers reviewed policies from eight countries and found that uptake varies widely. Some countries achieve high use by combining different approaches that affect both supply and demand. Supply-side strategies focus on how medicines are priced and purchased, such as through competitive tendering, where suppliers bid to provide medicines at lower cost. Demand-side strategies aim to influence behaviour, including education, financial incentives and prescribing targets for healthcare professionals. To better understand why some approaches work, the study applies Actor Network Theory, a framework that explains how different participants, including governments, clinicians, patients, and suppliers, interact within a system. It highlights a process called “translation,” where a central decision maker defines a goal, encourages others to align with it, and builds agreement across the network. Countries with the highest uptake either use strong, coordinated tendering systems or combine multiple policies that actively engage clinicians and patients. In contrast, countries that rely mainly on price controls tend to have lower uptake because they do not fully engage all parts of the system. Overall, the findings suggest that successful policies are those that align many different actors and create a stable, cooperative network that supports the use of biosimilar medicines.
Digital transformation presents a strategic imperative for the pharmaceutical industry, particularly within research and development (R D), where it promises accelerated time to market and enhanced operational efficiency. Building on the foundation of the People Coordination, Ownable Focus Areas, Long-Term Roadmap, Common Digital Alphabet, Reporting, and Monitoring (P.O.L.A.R.) Star framework, this article delves into the critical soft elements—human and organizational factors—essential for deploying a successful digital transformation in the pharmaceutical R D of a midsized company. While technological roadmaps provide structure and serve as a blueprint, sustainable results depend on an organization’s ability to evolve both in its culture and approach to change. In this context, implementing new capabilities—such as centralized R D data governance and a common data model—not only requires a transparent approach to data, strong digital leadership, and deep expertise but also triggers an organizational rethinking to support this evolution. Based on the needs and current evolution phase of the digital transformation journey of the company, this rethinking can be represented by a “federated” approach based on cross-functional teams, a digital unit to centralize activities and solutions, or a hybrid model combining elements of both. In summary, this article offers a focused, actionable guide to managing digital transformation in pharmaceutical R D. It explores the concept of a digital unit or a cross-functional team as strategic options, evaluated to guide intentional, structured operations within a digital reorganization; it also highlights the cultural shift needed for long-term sustainability.
In an era of rapidly evolving healthcare systems and escalating demands for value demonstration, pharmaceutical companies face unprecedented pressure to generate robust, relevant evidence for a diverse array of stakeholders. Traditional, siloed approaches to evidence generation are no longer sufficient. The development and use of integrated evidence generation plans (IEGPs) have emerged as strategic imperatives—reshaping how organisations align scientific, regulatory and patient-centred objectives across the product life cycle. The IEGPs bring together evidence-generation activities across functions and geographies, to ensure that robust evidence is delivered throughout the product life cycle. In this article, we present IEGP development as a collaborative and strategic process, which enables pharmaceutical companies to demonstrate the holistic value of a new therapy to a broader range of healthcare decision makers. We argue that Medical Affairs professionals are well positioned to lead this initiative, given their in-depth understanding of the evidence generation needs and priorities of patients and healthcare professionals; however, a close and strategic partnership with other key functions, including Market Access and Clinical Development, regions and countries, is vital to the holistic understanding of all key evidence needs and to establish the strategic differentiation required to bring new medicines to patients. Our companion article in this edition of Pharmaceutical Medicine expands on the role of specific subfunctions of Medical Affairs in the development of an IEGP; it also considers how the impact of Medical Affairs’ role can be measured. Please note that in both articles we prefer to use the term ‘IEGP’, but the reader may also see the similar term ‘IEP’ (Integrated Evidence Plan) used in the literature—these terms are used interchangeably in the field.
While there has been an increase in Duchenne muscular dystrophy (DMD) clinical trials over the last couple of decades, there is still no cure. Many individuals with DMD spend much of their lives participating in clinical trials. The impact of clinical trial participation on quality of life (QoL) is not well understood. This study aimed to understand the aspects of clinical trial participation that impact QoL for families affected by DMD. Qualitative interviews were conducted with patients aged ≥ 12 years and caregivers using a semi-structured interview guide. Participants described the clinical trial factors that impacted QoL and rated the impact of each factor using a 7-point Likert scale. Transcripts were single coded for themes. A Participant-Specific Total Impact Factor (PSTIF) score was derived using the mean score across factors identified as impacting QoL. Agreement was calculated using Cohen’s Kappa between PSTIF score and the participant’s reported net trial experience (positive, neutral, or negative). A total of 24 caregivers and 7 patients participated. Participants mentioned 23 clinical trial factors with an impact on QoL. While most participants (82
Schizophrenia is a complex neuropsychiatric disorder manifesting with diverse positive and negative symptoms as well as cognitive impairments. Current antipsychotics primarily address positive symptoms and frequently cause substantial side effects, highlighting the need for novel therapeutics targeting alternative pathomechanisms. Animal models are widely used to investigate schizophrenia's neurobiology and guide drug discovery, yet their clinical relevance for proof-of-concept (PoC) studies remains controversial. This Current Opinion critically examines the key limitations of animal models in schizophrenia research from a clinical perspective. The disorder’s multifaceted nature, involving genetic, environmental, and neurodevelopmental factors, makes accurate replication in animals challenging. Additionally, core human-specific symptoms, like hallucinations and thought disorders, cannot directly be modeled, although some underlying cross-species constructs can be operationalized. We argue that animal models are most informative when used to test specific, well-defined mechanistic hypotheses and when readouts are anchored to human-relevant biomarkers and neurophysiology, rather than interpreted as proxies for diagnostic categories. Accordingly, translational utility is not uniform: predictive performance depends on the induction paradigm, the construct validity of behavioral and neurophysiological readouts, and the clinical endpoint being modeled. We advocate for close collaboration between preclinical and clinical researchers to refine existing models, establish new and translationally relevant paradigms, and clearly define their interpretive scope. Integrating complementary advanced in vitro and in silico models may enhance mechanistic understanding and help prioritize hypotheses and candidates. Still, these approaches should be viewed as adjuncts, not superior replacements, because they cannot yet capture the circuit- and systems-level dynamics relevant to schizophrenia.
Digital transformation is increasingly shaping how the Medical Affairs (MA) function generates insights, engages stakeholders, and demonstrates value within the pharmaceutical industry. This article examines how MA professionals can navigate and lead the digital revolution reshaping healthcare delivery and stakeholder engagement. Digital maturity progresses from basic channel activation through tactical integration to advanced personalisation enabled by artificial intelligence (AI). Central to this transformation is the convergence of omnichannel engagement with real-world evidence generation, creating unprecedented opportunities to deliver personalised, scientifically rigorous interactions that enhance patient outcomes and healthcare professional (HCP) satisfaction. AI applications are creating new opportunities for MA to generate insights, communicate evidence, and measure impact across the healthcare ecosystem, enabling predictive analytics and intelligent content delivery at scale. Digital transformation is less likely to be effective when implemented through organisational silos. Important enablers include cross-functional collaboration, robust governance for responsible AI deployment, co-creation with external partners including HCPs and patient advocacy groups, and shared technology infrastructure that supports coordinated engagement. Best practices for digital communication strategies, fostering innovation cultures, and demonstrating measurable value are explored. As healthcare’s digital evolution accelerates, MA has an important role in ensuring that digital tools are applied in ways that remain scientifically rigorous, ethically governed, and aligned with stakeholder needs. By treating digital as an enabler of high-quality scientific exchange rather than an end in itself, MA can support more relevant engagement and strengthen the translation of evidence into practice.
For new investigational medicinal products (IMPs) entering clinical development, toxicity management guidelines (TMGs) can be developed as an addition to the clinical study protocol. These guidelines inform best clinical practice for the treatment of potential product-related toxicities including dose modifications and symptom management recommendations. TMGs ensure that early identification and intervention strategies are in place, helping to minimise risks and improve patient outcomes. Antibody-drug conjugates (ADCs) are a rapidly evolving drug class within oncology, and their accelerated development should be accompanied by high quality TMGs to support clinical trial success. Having a pre-prepared, 'off-the-shelf' set of TMGs for ADCs ensures consistency of care across several clinical trials investigating this drug class. The authors present a framework for developing these standardised TMGs across AstraZeneca's ADC portfolio. It incorporates information gathering from internal documents and published labels or guidelines, cross-product comparison, and standardisation decisions based on biological rationale and study/patient context. Although patient- and context-specific modifications remain necessary, a semi-standardised framework prioritises safety while allowing clinical judgment. Considerations for specific circumstances when the TMGs could be deviated from and how the approach can be extended to additional modalities and therapy areas are discussed.
One of the challenges in accessing cross-border clinical trials involving international participants in Europe is language diversity, with 32 official languages in the European continent. Some patients have reported being excluded from trials owing to their native language, and in certain studies, language has been used as an eligibility criterion for participation. Considering that pediatric studies in Europe are not conducted in all countries, cross-border access to clinical trials may represent the only therapeutic opportunity for children living with rare diseases for which no approved treatment exists. This study aimed to assess the use of language as an eligibility criterion in pediatric clinical trial protocols conducted in Europe (2007–2024) and published in the Clinicaltrials.gov database. It evaluated the frequency and context of language requirements and whether these were scientifically justified. The overall objective was to identify potential sources of language-based discrimination that may prevent cross-border access to pediatric clinical trials. The 32 official languages of the European continent were used as keywords to search the eligibility criteria of 1,754 pediatric clinical trial protocols for studies conducted in Europe between 2007 and 2024 and registered in the largest clinical trial registry, ClinicalTrials.gov, via an Application Programming Interface. Acceptable scientific justifications to use language as an eligibility criterion were defined as being (1) related to specific therapeutic areas that required language or cognitive assessments in communication with the health professionals, who do not speak the patient’s language or (2) related to the use of patient- or caregiver-reported outcome measures that had only been validated in specific languages. The majority of the study protocols (95.2
High-quality pharmacoepidemiological research is essential for credible real-world evidence (RWE). This expert consensus-based review explores how pharmaceutical Quality Management Systems (QMS) developed for studies using primary data collection (e.g., clinical trials, registries) can be adapted to support studies utilising secondary data to generate RWE, in line with regulatory expectations. The aim was to identify fit-for-purpose considerations for proportional oversight, data integrity, and regulatory-grade evidence generation. An international working group (WG) comprising RWE experts from industry, academia, and independent consultancy (including QMS specialist) assessed which elements of QMS frameworks developed for primary data collection are applicable to RWE studies utilising secondary data sources and those elements where adaptation would be required. Using the Nominal Group Technique, the WG identified and prioritised relevant quality systems and adaptation needs. In parallel, a targeted literature review of guidance and reports from International Coalition of Medicines Regulatory Authorities (ICMRA) member sites (focusing on the EU, USA and UK) assessed guidance against prioritized quality systems. Of 21 quality systems identified, 12 were considered most relevant to RWE studies utilising secondary data, with ten requiring contextual adaptations. The literature review identified 26 publications referencing one or more of these systems; quality manuals (69.2
Inherited metabolic disorders (IMDs) are rare genetic conditions that disrupt normal biochemical pathways, leading to potentially life-threatening metabolic imbalances. Early diagnosis, often through newborn screening, and treatment can significantly improve outcomes, but pharmacological management presents unique challenges that are amplified by developmental immaturity, altered pharmacokinetics, and heightened sensitivity to drug excipients. The selection of excipients becomes especially important in IMDs such as primary carnitine deficiency (PCD), where lifelong supplementation is required. Substances such as parabens, benzoates, saccharin sodium, propylene glycol, and ethanol are generally safe in adults, but may potentially contribute to metabolic crises or cumulative toxicity in neonates due to immature organ systems and altered metabolism. Current regulatory frameworks are addressing these concerns through guidelines, labelling revisions, and tools such as the STEP and SEEN databases, which compile paediatric safety data for excipients. Despite regulatory progress, significant gaps in excipient transparency, standardisation, and labelling persist, complicating clinical decision making. Healthcare providers often lack access to precise excipient concentrations and may unintentionally exceed safe thresholds in polypharmacy scenarios. This opinion paper underscores the critical need for age-appropriate, excipient-conscious drug formulations for children with IMDs. It advocates for improved regulatory oversight, increased formulation transparency, and interdisciplinary collaboration to minimise risk and enhance the safety of paediatric treatments, particularly for neonates requiring chronic therapy.
Bacteriophages (phages) are viruses that selectively kill bacteria and offer a promising option to address the growing global pandemic of antimicrobial-resistant infections. However, phage therapy does not easily align with traditional regulatory pathways designed for fixed-composition chemical drugs or biologics with fixed non-evolving compositions. Globally, alternative models such as personalised pharmacy-based formulations (known as magistral preparations), compassionate use provisions and flexible licensing have emerged to accommodate the biological complexity and personalised nature of phage-based therapeutics. Australia is well positioned to take a leadership role and consider a regulatory sandbox approach to the therapeutic use of phages that balances innovation with safety. Being time limited, this controlled framework would allow regulators and innovators to test new approaches under provisional rules and inform potential reforms. A sandbox should include strict participation criteria, and lead to the development of regulatory-ready biobanks of well-characterised phages, accelerating clinical access and manufacturing capacity. This model is a pragmatic and proactive approach that would enable safe scalable phage therapy in response to rising antimicrobial resistance threats.
Eye movement biomarkers are emerging as promising tools for monitoring neurodegenerative diseases in clinical trials. Saccadic hypometria, the reduced saccade amplitude leading to undershooting visual targets, is a recognized feature of Parkinson’s disease (PD), correlated with motor symptoms severity in cross-sectional studies. However, its use as a biomarker to monitor disease progression has not been studied. The aim was to assess the sensitivity and reproducibility of saccadic hypometria as a biomarker of PD progression. The amplitude of saccadic hypometria (ASH) was measured in two cohorts: a single-center cohort (SCC) (30 PD patients, 50 healthy controls) followed by a multicenter cohort (MCC) (250 PD patients, 91 healthy controls across 4 sites). Assessments occurred every 3 months over 9 months using a software-based platform (NeuraLight). Motor symptoms were assessed with the Movement Disorders Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) Part III. ASH and MDS-UPDRS changes were analyzed using individual slopes of change and compared between groups. ASH significantly declined over time in PD patients compared to controls in both cohorts (SCC: − 1.96 ± 4.14
Background A consistent and transparent approach is essential for quality decision-making in the review and approval of medicines. This is achieved through the use of a standard and well-defined framework, as the decisions made should not be influenced by any biases. While most National Medicines Regulatory Authorities (NMRAs) have designed frameworks to assess the quality of their decisions, many have not been implemented. A well-structured framework improves consistency and predictability in the decision-making process. The Quality of Decision-Making Orientation Scheme (QoDoS) has been widely adopted as a leading framework for this purpose. This study aimed to assess the decision-making processes of two technical committees operating within the Zambia Medicines Regulatory Authority (ZAMRA) using the QoDoS framework developed by the Centre for Innovation in Regulatory Science (CIRS); determine areas of improvement for routine assessment of quality of decision-making and its acceptability with respect to ZAMRA; and suggest ways of improving the lowest-scoring Quality Decision-Making Practices (QDMPs) and how these may be implemented into the decision-making framework to ensure consistency. Methods The framework was used to assess the quality of the decision-making process and subsequent implementation of the ten QDMPs. The study included five members from the Technical Committee for Human Medicines (TCHM) and seven members from the Technical Committee for Veterinary Medicines (TCVM) at ZAMRA, all responsible for recommending the approval or rejection of applications following scientific review. The validated QoDoS questionnaire was electronically distributed to the members, and data were analysed using descriptive statistics. Results Analysis of the QDMPs across the 12 committee members indicated that both human and veterinary medicines technical committees generally perceived their individual and organizational decision-making practices as favourable. Favourable QDMPs included QDMP 2 (assigning clear roles and responsibilities of the stakeholders involved in the review and approval of medicines), QDMP 4 (evaluate both internal and external influences or biases), QDMP 6 (considering uncertainty), QDMP 7 (re-evaluate new information as it becomes available), QDMP 9, (ensure transparency and keep a record trail) and QDMP 10 (effective communication of the basis of the decision). However, areas for improvement were identified in QDMP 1 (systematic structured approach), QDMP 3 (decision criteria), QDMP 5 (alternatives) and QDMP 8 (impact analysis) within the TCVM, as well as in QDMP 3 and QDMP 8 within the TCHM. Conclusion This study assessed committee members' perceptions of the implementation of QDMPs in the review and approval of medicines. It was demonstrated that most of the best QDMPs were implemented, except for four QDMPs that needed improvement, namely having a systematic structured approach, decision criteria, alternatives and impact analysis.
Lagging pediatric safety and effectiveness data increase the risks to children associated with off-label drug use. The objective of this study was to delineate the frequency of, and reasons behind, delays in the completion of mandated pediatric postmarketing requirement (PMR) studies. Publicly accessible and internal US Food and Drug Administration (FDA) data were aggregated to characterize pediatric PMRs issued from 2012 to 2024, including relevant dates, durations, and deferral extension (DE) requests. Sponsor size, and clinical trial enrollment status were also examined. There were 1160 pediatric PMRs identified, 459 of which were associated with 1176 DE requests. Despite a significant decline in the annual number of PMRs issued (slope [95
