New chemical entity development

Lead discovery, generation and optimization are basic activities in drug design which is devoted to identifying active new chemical entities, developing new active compounds and optimizing those able to be transformed into clinically useful drugs. 

The development of a single enantiomer as a new active substance should be described in the same manner as for any other new chemical entity. Studies should be carried out with the single enantiomer, but if development began with the race-mate then these studies may also be taken into account. Chiral conversion should be considered early on so that enantiospecific bioanalytical methods may be developed. These methods should be described in chemistry and pharmacy part of the dossier. If the opposite enantiomer is formed in vivo, then it should be evaluated in the same way as other metabolites. For endogenous human chiral compounds, enantiospecific analysis may not be necessary. The enantiomeric purity of the active ingredient used in preclinical and clinical studies should be stated. 

Based upon a review of the physical chemical properties of marketed drugs, Lipinski and coworkers have proposed an empirical rule of 5 (20). This rule may help pharmaceutical scientists in reaching an early decision about the potential candidacy for further development of a new chemical entity. The rule states that a chemical candidate is likely to display poor absorption or poor membrane permeability if... 

Fig. 37.1 Development process for a new chemical entity in the pharmaceutical industry.

The literature abounds with countless examples that illustrate how powder diffraction has been used to distinguish between the members of a polymorphic system. It is absolutely safe to state that one could not publish the results of a phase characterization study without the inclusion of XRPD data. For example, Fig. 7.11 shows the clearly distinguishable XRPD powder patterns of two anhydrous forms of a new chemical entity. These are easily distinguishable on the overall basis of their powder patterns, and one could place the identification on a more quantitative basis through the development of criteria similar to those developed for the mandelic acid system. 

For the present, the utilization of in vivo toxicological models is imperative for responsible risk assessment of new chemical entities. At the same time, the use of the many in vitro models currently available can serve as valuable adjuncts to these in vivo assessments, not only reducing the number of animals used in risk assessment, but providing unique information and possibilities for scientists involved in the drug discovery and development process. 

Irreversible CYP inhibition, especially when considered as a cause of chemically reactive metabolites, raises a number of issues that should be considered early in the drug discovery process. Careful evaluation of the structural features of the lead series as well as screening for MBIs early in the drug development process should guide series selection and optimization with the goal of avoiding the introduction of potentially risky moieties into new chemical entities. 

Clinical research groups are responsible for the discovery of new chemical entities, to target and interrupt disease pathways. It is common for drug products to come from families where the active backbone that targets the desired receptor is the same, and different side chains are added to achieve activity in the body. The development of thermodynamic methods that facilitate this approach will have an obvious advantage in reducing data requirements for the life science industries. 

When the first dosage form of either of a new chemical entity or generic product is developed, a dissolution method will... 

Drag development is a time-consuming and costly process. Recently, the need of very sensitive and selective assays for the complete characterization of New Chemical Entities (NCE) has become very stringent. 

The rather time- and cost-expensive preparation of primary brain microvessel endothelial cells, as well as the limited number of experiments which can be performed with intact brain capillaries, has led to an attempt to predict the blood-brain barrier permeability of new chemical entities in silico. Artificial neural networks have been developed to predict the ratios of the steady-state concentrations of drugs in the brain to those of the blood from their structural parameters [117, 118]. A summary of the current efforts is given in Chap. 25. Quantitative structure-property relationship models based on in vivo blood-brain permeation data and systematic variable selection methods led to success rates of prediction of over 80% for barrier permeant and nonper-meant compounds, thus offering a tool for virtual screening of substances of interest [119]. 

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