In-Silico Prediction of Drug Properties in Man Using Preclinical Data and Computer-Assisted Drug Development
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Drug Information Journal. Vol. 35. pp. 1047-1063. 2001
Copyright 0 2001 Drug Information Association Inc.
Printed in the USA. All rights reserved.
IN-SILICO PREDICTION OF DRUG PROPERTIES IN MAN USING PRECLINICAL DATA AND COMPUTERASSISTED DRUG DEVELOPMENT ROBERTOGOMENI,PHD, CHRISTINEFALCOZ,PHD, CARLAD'ANGELI,PHD, AND ALANBYE, PHD GIaxoSmithKline Group, GlaxoWellcome S.p.A., Verona, Italy
Computer-assisted drug development (CADD) is a knowledge-based process that integrates newly collected information in a drug/disease-specific knowledge frame and provides a rational basis for decision making during drug development. A mathematical model was developed to predict the dosage regimen appropriate to reach a desired human response for a new central nervous system compound from data collected in preclinical studies. The model incorporates uncertainty on the human pharmacokinetic/pharmacodynamic (PWPD) relationship scaled from animal data, including the afJinity adjustment derived from in-vitro receptor binding studies. Brain receptor occupancy, estimated using positron emission tomography imaging, was used as a surrogate marker of clinical efficacy. The CADD approach was used to design the first-time-in-man and the proofof-concept study. The expected minimal effective dose in man was estimated by simulating a dose-escalating trial, as the dose necessary to reach and maintain during chronic treatment is a target receptor occupancy of less than 70%, assuming that the therapeutic effect is associated with a receptor occupancy of less than 70%at a given probability level (Prob > 70%).Finally, the optimal in-vivo release characteristics from a pharmaceutical formulation were evaluated using a convolution-based model linking the in-vivo delivery rate to the PK/PD response, minimizing an appropriate cost function. Clinical trial simulation was used as a supportive tool for decision making by evaluating different scenarios accounting for the uncertainty in the predicted PK/PD relationship, intersubject variability, and drug potency. Key Words: Computer-assisted drug development; First-time-in-man; Proof-of-concept; Trial simulation; Minimal effective dose; Convolution-based model
INTRODUCTION THE lNCREASING PRESSURE to improve the operational efficiency of drug development drives pharmaceutical research toward the extensive use of new technologies. Clini-
Reprint address: Roberto Gomeni, GlaxoSmithKline Group, GlaxoWellcome, Via A. Fleming 4, 37135 Verona, Italy. E-mail: rog3 13900gsk.com.
cal trial simulation has been recently recognized as an effective tool for more effective drug development (1-4). This approach has been predominantly used in clinical development (Phase I to IV), and only occasionally used to optimize preclinical development or to ensure an optimal transition from preclinical to clinical development. On to continuThe ability from ously integrate any information collected
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Roberto Gomeni, Christine Falcoz, Carla
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