Drug Discovery and Development PHG 311. Prof. Dr. Amani S. Awaad

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1 Drug Discovery and Development PHG 311 Prof. Dr. Amani S. Awaad Professor of Pharmacognosy Pharmacognosy Department, College of Pharmacy Salman Bin Abdulaziz University, Al-Kharj. KSA.

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3 To Learn What is in silico? To understand relation between pharmacodynamic & pharmacokinetic To know roll of Absorption, Distribution, Metabolism, Excretion and Toxicity to understand the roll In silico ADME/Tox in drug discovery

4 In silico ADME/Tox in drug design Absorption Distribution Metabolism Excretion Toxicity

5 What is in silico' In silico ADME/Tox in drug design The term in silico' is a modern word usually used to mean experimentation performed by computer and is related to the more commonly known biological terms in vivo and in vitro. In silico pharmacology (also known as computational therapeutics, computational pharmacology) is a rapidly growing area that globally covers the development of techniques for using software to capture, analyse and integrate biological and medical data from many diverse sources. More specifically, it defines the use of this information in the creation of computational models or simulations that can be used to make predictions, suggest hypotheses, and ultimately provide discoveries or advances in medicine and therapeutics.

6 In silico ADME/Tox in drug design to build on the advances of the human genome, we need to integrate computational and experimental data, with the aim of initiating in silico pharmacology linking all data types. Basically, there are two outcomes when bioactive compounds and biological systems interact. drug that acts on a biological system can elicit a pharmacological and/or toxic response, in other words a pharmacodynamic (PD) event. Symmetrically, the biological system acts on the xenobiotic by absorbing, distributing, metabolising and excreting it. These are the pharmacokinetic (PK) events. The two basic modes of interaction between xenobiotics and biological systems, namely PD (activity and toxicity) and PK events (ADME)

7 In silico ADME/Tox in drug design Absorption, distribution and elimination will obviously have a decisive influence on the intensity and duration of PD effects, whereas biotransformation will generate metabolites that may have distinct PD effects of their own. Absorption Distribution Metabolism Excretion Toxiy Conversely, by its own PD effects, a compound may affect the state of the organism (for example, hemodynamic changes and enzyme activities) and hence its capacity to handle xenobiotics.

8 In silico ADME/Tox in drug design During many years, the drug discovery process involved chemical synthesis and in vivo testing with optimization of the compounds pharmacokinetic, metabolic and toxic properties postponed to later stages. Absorption Distribution Metabolism Excretion Toxiy In recent years there has been increasing awareness about the importance of predicting and optimizing the Absorption, Distribution, Metabolism, Excretion and Toxicity (ADME- Tox) properties of chemical compounds along the discovery process rather than at the final stages. Indeed, a study in the 1990s showed that several reasons could explain why drugs were failing in development. At that time, new chemical entities were essentially dropped because of poor pharmacokinetic properties, lack of efficacy and toxicity ADME/Tox Reasons for drug failure in Clinical Development (>80%)

9 In silico ADME/Tox in drug design But, the reasons for failures are still manifold: wrong target, poor pharmacokinetics, animal toxicity, lack of clinical efficacy, drug-drug interaction with other drugs, commercial reasons, formulation issues and adverse reactions in humans. Recent analysis suggests that over 90% of failures are now due to toxicity, with hepatotoxicity and cardiovascular implications alone causing two out of three market withdrawals

10 In silico ADME/Tox in drug design Although this kind of analysis and concepts about compound library profiling are still under debates, several studies suggest that a paradigm shift in drug discovery has occurred. One key challenge is to include in drug discovery campaigns (high-throughput and in silico screening) and whenever appropriate the right ADME/Tox property filtering. In addition, it is critical to simultaneously optimize binding affinity/selectivity, pharmacokinetic properties while avoiding toxicity. Prediction tools can thus assist both. It is of course important to find a balance between removing basically all molecules and retaining all. This is one of the reasons why we have an intermediate list where molecules are only flagged and not added to the rejected list. Guide optimisation based on in silico models Screening, hit-optimization, lead selection, lead optimization, SOPP, development Validate/refine models based on new pharmacological data

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