The Takeda Pharmaceutical Company Limited (武田薬品工業株式会社, Takeda Yakuhin Kōgyō kabushiki gaisha) [takeꜜda jakɯçiŋ koꜜːɡʲoː] is a Japanese multinational pharmaceutical and biopharmaceutical company. It is the largest pharmaceutical company in Asia and one of the top 20 largest pharmaceutical companies in the world by revenue (top 10 following merger with Shire). The company has over 49,578 employees worldwide and achieved US$19.299 billion in revenue during the 2018 fiscal year. The company is focused on metabolic disorders, gastroenterology, neurology, inflammation, as well as oncology through its independent subsidiary, Takeda Oncology. Its headquarters is located in Chuo-ku, Osaka, and it has an office in Nihonbashi, Chuo, Tokyo. In January 2012, Fortune Magazine ranked the Takeda Oncology Company as one of the 100 best companies to work for in the United States.
This post-marketing surveillance study assessed the safety and effectiveness of guanfacine hydrochloride extended-release (GXR) in adults with attention-deficit/hyperactivity disorder (ADHD) in routine clinical practice in Japan. In this prospective, multicenter study, adults (≥ 18 years) were followed for 1 year after initiating GXR treatment or until treatment discontinuation, whichever occurred first (enrollment: June 2020–March 2022). Hypotension and bradycardia, syncope, blood pressure elevation upon discontinuation, and QT prolongation were key safety concerns for evaluation. Missing data were not imputed; therefore, effectiveness outcomes reflect only the observed data. In total, 961 patients were enrolled across 155 sites; case report forms were collected for 949 patients. Of these, 912 and 784 were included in the safety and effectiveness analyses, respectively. The 12-month GXR continuation rate was 45.2
The number of clinical investigations and approved applications of adeno-associated virus (AAV) based transgene product (TP) delivery has grown steadily. There also has been a growing interest in understanding how anti-AAV and anti-TP immune responses affect the safety and efficacy of these gene therapy treatments. While considerations related to anti-AAV immunity have been discussed in other works, this manuscript focuses on the assessment of anti-TP immune responses, including both humoral and cellular responses. The development of anti-TP antibodies or a cytotoxic cellular response may lead to increased clearance of the TP, elimination of AAV-transduced cells, and consequently, affect the overall durability and efficacy of the treatment. Additionally, the binding and neutralization of residual endogenous protein by anti-TP antibodies might further worsen the clinical condition under treatment. Several topics are explored in this manuscript, including immunogenicity risk factors that can be considered when evaluating the overall risk and impact of anti-TP immunogenicity, potential implications of anti-TP immunogenicity, the importance of assessing anti-TP immunogenicity, and the commonly used analytical methodologies. The manuscript proposes an approach to determining the scope of anti-TP immunogenicity assessment for clinical and non-clinical studies, based on the TP nature, other intrinsic and extrinsic risk factors. Authored by a group of scientists involved in AAV-based therapeutic development from various industry organizations, the manuscript aims to provide recommendations and guidance to industry sponsors, academic laboratories, and regulatory agencies working on AAV-based modalities, with the goal of achieving a more consistent approach to the assessment of anti-TP immune response.
BACKGROUND:Patients with short bowel syndrome (SBS)-associated intestinal failure (SBS-IF) are dependent on parenteral support (PS). In Japan, teduglutide is the only GLP-2 analog medicine indicated for these patients. There are limited data for pediatric patients, especially those with a low body weight. This study evaluated the safety and efficacy of teduglutide in Japanese pediatric patients with SBS-IF (dependence on PS to provide ≥30% of fluid or caloric intake needs) who weighed less than 10 kg. METHODS:This phase 3, open-label study enrolled Japanese pediatric patients with SBS-IF. Patients weighing less than 10 kg received teduglutide 0.05 mg/kg/day subcutaneously in 28-week treatment cycles (24 weeks of teduglutide treatment and 4 weeks of follow-up). Adverse events, changes in PS requirements, and growth parameters were assessed. RESULTS:Three patients completed the study, with a mean teduglutide exposure duration of 48.9 weeks. All patients experienced treatment-emergent adverse events (TEAEs), but none were related to the study drug or led to death or treatment discontinuation. Clinically meaningful reductions in mean PS volume (13.1%) and mean PS caloric intake (46.6%) were observed at the end of treatment from baseline. One patient achieved a reduction in PS volume of ≥20% at the end of treatment from baseline. Growth parameters showed increases in weight and height/length-for-age z-scores at the end of treatment from baseline. CONCLUSION:In the three patients with SBS-IF who weighed less than 10 kg, no new safety signals were observed following teduglutide treatment. Clinically meaningful reductions in PS were noted and there was no adverse impact on growth parameters. TRIAL REGISTRATION:ClinicalTrials.gov registration number: NCT05027308.
Advances in machine learning and artificial intelligence have recently extended to the quantitative prediction of drug-drug interaction (DDI). Because DDIs arise from diverse mechanisms and the required level of predictive accuracy varies with both the endpoint and the stage of drug development, evaluating their significance and deciding what is needed demand unusually broad expertise-ranging from fundamental biology all the way to state-of-the-art machine-learning methods. In this review, DMPK scientists with expertise in machine learning survey and critique the most recent literature covering the following DDI categories: Cytochrome P450 (CYP) substrates, CYP competitive and time-dependent inhibition, CYP induction, non-CYP substrates, non-CYP inhibition, transporter substrates, transporter inhibition, and cutting-edge predictive algorithms based on deep learning applied for the task of DDIs. For each category we summarize current in silico methodologies and their performance, and we provide expert opinions on how these tools can be optimally incorporated into contemporary drug-discovery workflows.
Monoclonal antibody (mAb) titer monitoring is a key capability during process development and optimization, enabling timely decision making and increasing the speed of development. Raman spectroscopy is a prominent process analytical technology (PAT), but resource-efficient calibration strategies for the development of transferable models are limited. This work demonstrates the development and successful transfer of a calibration model for monoclonal antibody concentration between two different cell lines with varied metabolic profiles expressing different antibodies. The root mean square error of prediction (RMSEP) for titer in the source cell line (0.266 g L-1) was comparable to that of the target cell line (0.325 g L-1). The transferable model was achieved by conducting a spiking study in a high-throughput parallel bioreactor system. Different experimental approaches with models trained on spiked versus native samples were compared. This analysis revealed that model transferability was influenced by the degree of correlation of lactate with antibody titer in the source process, emphasizing the importance of process knowledge in the development of Raman calibration models. Overall, the study presents evidence of the feasibility of transferable titer models, marking a significant advancement in process monitoring capabilities for high-throughput cell culture as well as introducing a generic methodology for calibration of transferable models in the context of upstream bioprocessing.
