Application of predictive biosimulation within pharmaceutical clinical development: examples of significance for translational medicine and clinical trial design
Abstract
The challenge of accurately predicting human clinical outcome based on preclinical data has led to a high failure rate of compounds in human clinical trials. A series of methods are described by which biosimulation can address these challenges and guide the design and evaluation of experimental and clinical protocols. Early compound development often proceeds on the basis of preclinical data from animal models. The systematic evaluation possible in a simulation can assist in the critical step of translating the preclinical outcomes to human physiology. Later in the process, clinical trials definitively establish a therapy's beneficial effects, as well as any adverse side effects. Biosimulation allows for the optimal design of clinical trials to ensure that key issues are addressed effectively and efficiently, and in doing so, improves the success rate of the trials.
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The T2DM QSP model article estimated a reduction in 66% of the cost and 40% of the time length of the phase I trial.
“The article on the T2DM QSP model mentioned previously80 is an example of reporting this sort of impact: the authors estimated a reduction in 66% of the cost and 40% of the time length of the phase I trial.”
Entelos QSP simulations for a first-in-class therapy against type 2 diabetes mellitus led to a reduction from a 6-arms-for-14-weeks design to a 2-arms-for-8-weeks phase I clinical trial design.
“A good example of the latter was reported by Entelos80 in their publication78 about the optimization of a phase I clinical trial protocol for a first‐in‐class therapy against type 2 diabetes mellitus (T2DM): their QSP simulations led to the reduction from a “6 arms for 14 weeks” to a “2 arms for 8 weeks” design.”
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References 4 · Cited by 32
- Authors
- Kansal, A. R., & Trimmer, J.
- Venue
- IEE Proceedings - Systems Biology
- Published
- 2005
- Volume
- 152
- Issue
- 4
- Pages
- 214
- ISSN
- 1741-2471 (ISSN-L)
- OpenAlex
- W2025654004
- Cited by
- 32
- References
- 4
- Citations by year
- 2023: 2 · 2021: 1 · 2020: 1 · 2019: 2 · 2018: 1 · 2017: 2 · 2016: 3 · 2013: 1 · 2012: 2
- FWCI
- 3.45
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Systems Biology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Health Sciences › Veterinary › Small Animals › Animal testing and alternatives
- Health Sciences › Medicine › Pediatrics, Perinatology and Child Health › Pharmaceutical studies and practices
- Keywords
- translational medicine, clinical trial design, animal models, clinical trial success rates, adverse drug reactions, human physiology
- MeSH terms
- Animals, Biological Assay, Clinical Trials as Topic, Computer Simulation, Diabetes Mellitus, Disease Models, Animal, Drug Industry, Drug Evaluation, Preclinical, Glycogen, Humans, Insulin, Liver, Male, Models, Biological, Research Design, Species Specificity, Drug Design, Rats, Wistar, Rats
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