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Opportunities and Challenges of Disease Progression Modeling in Drug Development – An IQ PerspectiveGoteti, Kosalaram; Hanan, Nathan; Magee, Mindy; Wojciechowski, Jessica; Mensing, Sven; Lalovic, Bojan; Hang, Yaming; Solms, Alexander; Singh, Indrajeet; Singh, Rajendra; Rieger, Theodore Robert; Jin, Jin Y.
Clinical pharmacology and therapeutics, August 2023, 2023-Aug, 2023-08-00, 20230801, Volume: 114, Issue: 2Journal Article
Disease progression modeling (DPM) represents an important model‐informed drug development framework. The scientific communities support the use of DPM to accelerate and increase efficiency in drug development. This article summarizes International Consortium for Innovation & Quality (IQ) in Pharmaceutical Development mediated survey conducted across multiple biopharmaceutical companies on challenges and opportunities for DPM. Additionally, this summary highlights the viewpoints of IQ from the 2021 workshop hosted by the US Food and Drug Administration (FDA). Sixteen pharmaceutical companies participated in the IQ survey with 36 main questions. The types of questions included single/multiple choice, dichotomous, rank questions, and open‐ended or free text. The key results show that DPM has different representation, it encompasses natural disease history, placebo response, standard of care as background therapy, and can even be interpreted as pharmacokinetic/pharmacodynamic modeling. The most common reasons for not implementing DPM as frequently seem to be difficulties in internal cross‐functional alignment, lack of knowledge of disease/data, and time constraints. If successfully implemented, DPM can have an impact on dose selection, reduction of sample size, trial read‐out support, patient selection/stratification, and supportive evidence for regulatory interactions. The key success factors and key challenges of disease progression models were highlighted in the survey and about 24 case studies across different therapeutic areas were submitted from various survey sponsors. Although DPM is still evolving, its current impact is limited but promising. The success of such models in the future will depend on collaboration, advanced analytics, availability of and access to relevant and adequate‐quality data, collaborative regulatory guidance, and published examples of impact.
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