Impact of Model-Informed Drug Development on Drug Development Cycle Times and Clinical Trial Cost.

IF 6.3 2区 医学 Q1 PHARMACOLOGY & PHARMACY
Vaishali Sahasrabudhe, Timothy Nicholas, Gianluca Nucci, Cynthia J Musante, Brian Corrigan
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引用次数: 0

Abstract

Model-informed drug development (MIDD) integrates data to quantify benefit/risk informing objective drug discovery and development decisions. An additional critical benefit of MIDD is postulated to be improvement in trial and program efficiencies. While the application of MIDD has grown, there have been no clear examples across programs to demonstrate its value at the portfolio level. This manuscript offers a methodology and examples to demonstrate MIDD value in terms of time and cost savings. We utilized an algorithm to estimate savings based on MIDD-related activities at each stage of development across the entire drug development portfolio during a typical year between 2021 and 2023. This algorithm, although company-specific, demonstrated general applicability across several programs of the portfolio. Overall, the use of MIDD yielded annualized average savings of approximately 10 months of cycle time and $5 million per program. Systematic application of MIDD approaches yielded significant time and cost savings across the drug development portfolio in addition to informing data-driven decisions. Increased utilization of MIDD approaches is a driver for improving drug development efficiency.

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来源期刊
CiteScore
12.70
自引率
7.50%
发文量
290
审稿时长
2 months
期刊介绍: Clinical Pharmacology & Therapeutics (CPT) is the authoritative cross-disciplinary journal in experimental and clinical medicine devoted to publishing advances in the nature, action, efficacy, and evaluation of therapeutics. CPT welcomes original Articles in the emerging areas of translational, predictive and personalized medicine; new therapeutic modalities including gene and cell therapies; pharmacogenomics, proteomics and metabolomics; bioinformation and applied systems biology complementing areas of pharmacokinetics and pharmacodynamics, human investigation and clinical trials, pharmacovigilence, pharmacoepidemiology, pharmacometrics, and population pharmacology.
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