CDER-What’s New in Regulatory Science-Issue 1, 2026 (+++++) +...

5-FY26 Nonclinical Human Cardiac New Approach Methodologies (NAMs) Predict Vanoxerine-Induced Proarrhythmic Potential https://pubmed.ncbi.nlm.nih.gov/40863351/ Garcia MI, Bhardwaj B, Dame K, Charwat V, Siemons BA, Goswami I, Ismaiel OA, Mistry S, Feaster TK, Healy KE, Ribeiro AJS, Blinova K. J Cardiovasc Dev Dis. 2025 Jul 26;12(8):285. Cardiac New Approach Methodologies (NAMs) were evaluated for their ability to detect drug-induced cardiac arrhythmic events that were not identified in nonclinical animal models or Phase I-II clinical trials. More specifically, the NAM utilized human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) and electrophysiological measurements. The drug examined, vanoxerine, has known cardiac risks that were not detected until late-stage clinical trials. In this study, researchers demonstrated for the first time that this compound triggered proarrhythmic events in a human-relevant nonclinical model. These findings demonstrate that this nonclinical cardiac NAM can successfully recapitulate clinical outcomes associated with vanoxerine. 6-FY26 Nitrosamine Ames Data Review and Method Development: Proceedings of a US FDA/HESI Workshop https://pubmed.ncbi.nlm.nih.gov/41689482/ Atrakchi, Aisar; Puglisi, Raechel; Bercu, Joel; Cheung, Jennifer; Czich, Andreas; Froestchl, Roland; Davis-Bruno, Karen; Heflich, Robert H; Kobets, Tetyana; McGovern, Timothy J; Lynch, Anthony; Selby, Max; Schuler, Maik; Silveira, Gabriela De Oliveira; Vespa, Alisa; Whomsley, Rhys; Chen, Connie L. Mutagenesis. 2026 Jun 27;41(4):225-236. Due to concerns over the sensitivity of the standard Ames test (OECD Test Guideline 471) in detecting the mutagenic and carcinogenic potential of N-nitrosamines (NAs) — including NA Drug Substance-Related Impurities (NDSRIs) found in marketed pharmaceuticals — the FDA's Center for Drug Evaluation and Research (CDER) Office of New Drugs (OND) and the Health and Environmental Sciences Institute's Genetic Toxicology Technical Committee (HESI/GTTC) co-organized a workshop to discuss optimized Ames test conditions for evaluating NAs and NDSRIs, with sessions addressing key parameters such as metabolic activation methods and tester strain selection. This report summarizes the key takeaways from that workshop. 7-FY26 Beyond QSARs: Quantitative Knowledge-Activity Relationships (QKARs) for enhanced drug toxicity prediction https://pubmed.ncbi.nlm.nih.gov/41025529/ Li, Ting; Qu, Yanyan; Chen, Alexander; Thakkar, Shraddha; Li, Dongying; Tong, Weida. Toxicol Sci. 2025 Dec 1;208(2):269–278. This study introduces Quantitative Knowledge-Activity Relationships (QKARs), a novel computational framework that predicts drug toxicity using domain-specific knowledge rather than relying solely on chemical structure as traditional Quantitative Structure-Activity Relationships (QSARs) do. QKAR models were developed for two key toxicity endpoints, drug-induced liver injury (DILI) and drug-induced cardiotoxicity (DICT). Leveraging the advances in AI, including text embedding and generative AI, were found to consistently outperform QSARs, particularly in distinguishing drugs with similar structures but different toxicity profiles. The study also explored integrating knowledge-based and structure-based representations (Q(K+S)ARs), demonstrating that QKARs offer a robust and promising alternative to QSARs for enhanced drug toxicity prediction and risk assessment. 8-FY26 Optimizing Oligonucleotide Therapeutics: A Model-Informed Drug Development Perspective https://pubmed.ncbi.nlm.nih.gov/42083118/ Yuan, Ye; Sharma, Vishnu; Bhattaram, Venkatesh Atul; Pan, Xiaolei; Earp, Justin; Wang, Yun; Liu, Jiang; Zhu, Hao. Clin Transl Sci. 2026 May;19(5):e70570 Oligonucleotide therapies, including antisense oligonucleotides (ASOs), small interfering RNAs (siRNAs), and aptamers, present unique drug development challenges, particularly the disconnect between systemic exposure and tissue activity, where these therapeutics are rapidly cleared from circulation yet persist intracellularly with sustained effects, complicating dose optimization and efficacy prediction especially given limited clinical data from rare disease indications. This review examines how Model-Informed Drug Development (MIDD) has emerged as a critical solution to these challenges across FDA-approved oligonucleotide therapies, demonstrating how quantitative modeling has been successfully applied to bridge the PK-PD disconnect, inform endpoint selection for accelerated approvals, guide dosing strategies for general and special populations, and ultimately advance the clinical and regulatory success of this therapeutic class. 9-FY26 Using real-world data to predict findings of an ongoing phase IV trial: glycemic control of semaglutide versus standard of care https://pubmed.ncbi.nlm.nih.gov/41161770/ Kattinakere Sreedhara S, Schneeweiss S, D'Andrea E, Weberpals JG, DiCesare EC, Patorno E, Tsacogianis T, Bradley M, Concato J, Wang SV. BMJ Open Diabetes Res Care. 2025 Oct 29;13(5):e005180. Using national claims data (Optum Clinformatics, 2017–2022), this study emulated the design of the ongoing SEPRA trial to compare once-weekly injectable semaglutide against standard-of-care (SoC) medications for glycemic control (A1C <7%) in adults with type-2 diabetes on metformin monotherapy. Among 1,144 propensity score-matched pairs, semaglutide initiators were 30% more likely to achieve glycemic control (RR 1.30, 95% CI: 1.16–1.45) and showed a slightly greater A1C reduction (1.3% vs. 1.1%) compared to SoC, findings that were consistent with interim SEPRA trial results released after the study protocol was preregistered. These results support the value of well-designed, preregistered non-randomized studies using fit-for-purpose real-world data as effective complements to pragmatic randomized controlled trials. Impact Stories https://www.fda.gov/drugs/regulatory-science-action/impact-stories?utm_medium=email&utm_source=govdelivery