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CPSA Digest 2001

New Technologies and Approaches for Increasing Drug Candidate Survivability:
Lead Identification to Lead Optimization

October 9-11, 2001

CPSA Digest 2001

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Proceedings -Wednesday, October 10, 2001

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The New Pre-Preclinical Program in Drug Discovery

John Masucci, RW Johnson Research Institute

Background:
The development process for new drugs is a lengthy one in the United States (10 yr or more). Often, it can take from 3-7 years for a new chemical entity (NCE) to reach IND status. Also, to reach this plateau, an attrition rate of 87% is encountered, documenting that reasons for termination are not found early enough in the development cycle. Major reasons for termination are shown below.

Premise:
This unacceptable termination rate of NCEs can also be attributed to poor correlation (poor prediction ability) between two important groups of obtained data: comparisons of human in vitro and in vivo data, and in vivo (animal) data compared with in vivo (human) data. While many years ago the drug discovery process involved simply screening of synthesized compounds for activity, it is clear that today the drug discovery process must include assessment and accurate prediction of ADME properties before the IND stage in order to better identify lead compounds. The integration of "pre-preclinical" into drug discovery will result in the selection of optimized NCEs for further development.

As an example, the suggested assays (screens) to use in drug discovery for a more thorough evaluation of NCEs may include the following in vitro and in vivo analyses: fast and standard pharmacokinetics (rat), toxicokinetics, metabolite identification, Ames assays (toxicity), CNS evaluation, cardiovascular toxicity, cerep selectivity, P450 inhibition, human liver microsomal metabolism, and an assessment of physical properties.

Future
As a result of integrating animal efficacy data, in vivo and in vitro pharmacokinetic data, and many other ADME data generated early in the discovery phase, it is hoped that drug development teams will be able to model a compound's behavior in Man. The end result of this process, performed with more accurate and predictive data, will be to nominate a more robust preclinical drug candidate worthy of a continued investment of time and money by a pharmaceutical organization.

Links
S. Venkatesh and R.A. Lipper, "Role of the Development Scientist in Compound Lead Selection and Optimization", Journal of Pharmaceutical Sciences, 89(2):145-54, February 2000.

"Drug Discovery: Filtering Out Failures Early in the Game", Chemical & Engineering News, 78(23):63 June 5, 2000.

Ronald T. Borchardt, "Integrating Drug Discovery and Development", The Scientist 15(5):43 (March 5, 2001).



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