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Virtual Populations for Quantitative Systems Pharmacology Models.
Cheng, Yougan; Straube, Ronny; Alnaif, Abed E; Huang, Lu; Leil, Tarek A; Schmidt, Brian J.
Affiliation
  • Cheng Y; QSP and PBPK, Bristol Myers Squibb, Princeton, NJ, USA.
  • Straube R; Daiichi Sankyo, Inc., Pennington, NJ, USA.
  • Alnaif AE; QSP and PBPK, Bristol Myers Squibb, Princeton, NJ, USA.
  • Huang L; QSP and PBPK, Bristol Myers Squibb, Princeton, NJ, USA.
  • Leil TA; EMD Serono, Billerica, MA, USA.
  • Schmidt BJ; QSP and PBPK, Bristol Myers Squibb, Princeton, NJ, USA.
Methods Mol Biol ; 2486: 129-179, 2022.
Article in En | MEDLINE | ID: mdl-35437722
Quantitative systems pharmacology (QSP) places an emphasis on dynamic systems modeling, incorporating considerations from systems biology modeling and pharmacodynamics. The goal of QSP is often to quantitatively predict the effects of clinical therapeutics, their combinations, and their doses on clinical biomarkers and endpoints. In order to achieve this goal, strategies for incorporating clinical data into model calibration are critical. Virtual population (VPop) approaches facilitate model calibration while faced with challenges encountered in QSP model application, including modeling a breadth of clinical therapies, biomarkers, endpoints, utilizing data of varying structure and source, capturing observed clinical variability, and simulating with models that may require more substantial computational time and resources than often found in pharmacometrics applications. VPops are frequently developed in a process that may involve parameterization of isolated pathway models, integration into a larger QSP model, incorporation of clinical data, calibration, and quantitative validation that the model with the accompanying, calibrated VPop is suitable to address the intended question or help with the intended decision. Here, we introduce previous strategies for developing VPops in the context of a variety of therapeutic and safety areas: metabolic disorders, drug-induced liver injury, autoimmune diseases, and cancer. We introduce methodological considerations, prior work for sensitivity analysis and VPop algorithm design, and potential areas for future advancement. Finally, we give a more detailed application example of a VPop calibration algorithm that illustrates recent progress and many of the methodological considerations. In conclusion, although methodologies have varied, VPop strategies have been successfully applied to give valid clinical insights and predictions with the assistance of carefully defined and designed calibration and validation strategies. While a uniform VPop approach for all potential QSP applications may be challenging given the heterogeneity in use considerations, we anticipate continued innovation will help to drive VPop application for more challenging cases of greater scale while developing new rigorous methodologies and metrics.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Pharmacology / Network Pharmacology Type of study: Prognostic_studies Language: En Journal: Methods Mol Biol Journal subject: BIOLOGIA MOLECULAR Year: 2022 Document type: Article Affiliation country: Estados Unidos Country of publication: Estados Unidos

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Pharmacology / Network Pharmacology Type of study: Prognostic_studies Language: En Journal: Methods Mol Biol Journal subject: BIOLOGIA MOLECULAR Year: 2022 Document type: Article Affiliation country: Estados Unidos Country of publication: Estados Unidos