Rational drug discovery process starts with two lines of research, which are largely independent and run in parallel, besides, they belong to various domains of life sciences and utilize distinctly different methods  – biological (target identification and validation, design of activity tests) and chemical (design of new molecules, hit identification and lead development). While these activities in principle belong to standard exploratory programs performed in innovative big pharma companies under confidentiality clause,  they are also a subject of open academic research and even university teaching. Nevertheless, the vast effort of pure and applied sciences combined, bears scanty fruit – number of new launches of innovative drugs remains  at unimpressive level of 20 + annually. Although we have better tools than ever in our disposal, including genomics and proteomics on one side and combinatorial chemistry and high throughput screening on the other, the output of pharmaceutical R&D remains well below needs and expectations. It is generally agreed that high attrition rate in the drug discovery and development  (DDD) process results mainly from inadequate generating, acquisition and processing of data around the merger point of  the two lines of research mentioned above, that is  between establishing the lead structure and clinical verification of validated drug candidate. This segment of DDD research, generally described as pre-clinical evaluation, is rather poorly regulated and tendency for regarding particular requirements as „project specific” seems to prevail. Based on case studies and individual experience, we put forward a sequence of task, for an unspecified DDD project, which can lead to safe „first-in-man” application of an investigational new drug, based on regulatory submission.  Anotherwords, a set of advices is formulated and discussed, which indicates how to transform a new molecular entity (NME), into properly specified and certified active pharmaceutical ingredient (API), fit for experimental pharmaceutical formulation and manufacturing of clinical batches. At first, “druggability” of a new molecule has to be evaluated, using structural analysis backed up by physicochemical measurements, spectroscopic methods, polymorphism study, SAR analysis, metabolism predictions etc. Then, even more complex tasks follow, with design of biological activity tests at molecular, cellular, tissue and organism levels. Mechanism of biological activity has to be established, biodistribution and metabolism evaluated and pharmacokinetic data determined in an animal model. Last but not least, acute toxicity in two animal species lead to “go/no go” decision point on the road to clinical experiment. Since all these studies have in principle to be carried out under quality assurance system, an interplay between requirements for the tested substance and validation of analytical methods and biological tests, assuring validity of the experimental data, becomes an essential issue in the preclinical segment of drug discovery process.

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