Preclinical lead optimization

These preclinical lead optimization technologies (PLOT S), must be sufficiently rapid to interface with high-throughput screens without creating a further pipeline bottleneck, be predictive of drug failure, and... 

Lead Optimization in Pharmaceutical Development Molecular and Cellular Approaches Preclinical lead optimization models Sev. 1 or 2... 

More recently, the bottleneck of drug research has shifted from hit-and-lead discovery to lead optimization, and more specifically to PK lead optimization. Some major reasons are (i) the imperative to reduce as much as feasible the extremely costly rate of attrition prevailing in preclinical and clinical phases, and (ii) more stringent concerns for safety. The testing of ADME properties is now done much earlier, i.e. before a decision is taken to evaluate a compound in the clinic. 

From a DMPK perspective, a common goal is to be able to compare multiple compounds based on their absorption, distribution, metabolism and excretion (ADME) properties as well their preclinical PK properties [8, 12-22]. Therefore, lead optimization typically is performed as an iterative process that uses the DMPK data to select structural modifications that are then tested to see whether the DMPK properties of the series have been improved. This iterative process is shown schematically in Fig. 13.2. Clearly an important element for the successful lead optimization of a series of NCEs is the ability to perform the DMPK assays in a higher throughput manner. The focus of this chapter will be to discuss ways that mass spectrometry (MS), particularly HPLC-MS/MS can be used to support the early PK studies for NCEs in a higher throughput manner. 

The principal issue in the drug discovery process is the high failure rate in the clinical trials, mainly due to liabilities related to poor pharmacokinetics (PK), poor efficacy, and high toxicity. The earlier lead optimization (LO) phase then represents a crucial step in the drug discovery process, since it involves the preparation and the selection of suitable drug candidates. In view of the increasing need for speed in the preclinical research and development, the determination of activity and selectivity is performed simultaneously with the evaluation of pharmacokinetic and toxicity properties. This multiparametric approach allows the early selection of the compounds with the best overall balanced druglike profile [1]. 

After optimization, scientists test the lead compounds in more sophisticated models including pharmacokinetics, pharmacodynamics, and toxicity. The optimal molecule selected from these assessments is then declared a new dmg candidate and moves on to the next phase (development). If a program is successful, it may take a total of 3-6 years from target selection and validation through lead generation, lead optimization, and preclinical evaluation in animals to candidate selection for a potential new medicine. 

Fig. 3 Diagramatic representation of Old and New strategies for lead optimization of new pharmaceutical molecules. The top section indicates the Old (and in some cases, current) way in which pharmaceutical companies take Hits to lead development candidate through discovery and early preclinical development testing. Essentially, no high-throughput formal lead optimization exists in this model but is developed for backup compounds by using biomarkers identified during lead compound failure in vivo. The bottom section indicates the New way forward (used now by most major pharmaceutical companies). In this model, a formal in vitro PLOT battery is inserted early in development before preliminary in vivo ADME-Tox screening and subsequent lead development candidate selection.

In addition, when considering pharmaceutical compounds requiring intravenous, ocular or topical routes of administration as a strategic part of their development plan, then the same consideration for early in vitro screening should be made. In fact, if the final development plan for a particular therapeutic class indeed required such routes, then the lead optimization process (or some later preclinical selection step) could screen for these eventualities at an early stage. 

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