Bioinformatica 15-12-2011-t9-t10-bio cheminformatics
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The document outlines the schedule and content for a bioinformatics course. It includes 10 lessons covering topics like biological databases, sequence alignments, database searching, phylogenetics, and protein structure. It also mentions that the final exam will include randomly generated images from a set of 713 images.
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Drug discovery and development is a long, expensive, and complex process averaging about 12 years and $500 million to bring a new prescription medication to market. Only 1 in 10,000 compounds eventually becomes an approved drug. The process involves discovery, preclinical research, clinical trials, and regulatory approval. Discovery aims to identify candidate drug molecules, while preclinical research studies their safety and efficacy in animal models before human testing. Clinical trials then evaluate new drugs with patients for safety and effectiveness over several phases before regulatory approval and marketing.
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The process is based on the use of bio-microassays that are rapid to carry out and require very small quantities of the reagents and test compound.
These assays are carried out on 96- and bigger-well plates using specialised handling equipment.
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These Targets ranging from gene mutations, mRNA levels, protein levels, DNA, RNA and enzyme activities.
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The document discusses the Collaborative Drug Discovery (CDD) platform, which aims to facilitate data sharing and collaboration in drug discovery. Key points:
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Opensourcepharma Dr Nibedita rath
Access to Research
Date 11-08-2018
Venue Conference HAll NIAS IISc campus
Conference and workshops for clinical practitioners to introduce them to modern tools and an alternative approach to modern scientific research.
Purpose
1. Build a network of physicians across the country
2 Train physicians to analyse clinical data and restructure it to make it compatible with research standards
3. Introduce modern tools to understand the mechanism of actions of medicine
4. Introduce artificial intelligence and machine learning to clinical practitioners to support decision-making processes
Access to Science
Clinical experience and traditional knowledge are important sources of data that affect decision making processes in modern healthcare systems. This data should be made accessible for scientific evaluation and validation to improve healthcare worldwide. The Open Source Pharma Foundation believes that clinical practitioners from various disciplines should have the right to access research so that they can help identify problems, contribute their scientific knowledge, and support the discovery ecosystem.
Background
The majority of medical practitioners working on the ground level with patients do not take part in open clinical research worldwide. However, the data collected and owned by them plays an important role in establishing better discovery pathways. Through this workshop, we seek to open opportunities to enhance health care systems around the world and to overcome the following challenges faced by medical practitioners.
1. Regulatory limitations
2. Academic limitations
3. Time constraints
4. Lack of access to modern tools
new drug discovery studies
New Drug Design & Discovery discusses the process of drug discovery and design. It begins with an introduction to how drugs work in the human body to modulate functions. The drug discovery process is then described as a long, expensive endeavor involving chemical synthesis, clinical development, and formulation. Computer-aided drug design uses molecular modeling and structure-based approaches to predict ligand-receptor binding and identify biological targets in silico. Combinatorial chemistry and high-throughput screening allow for the rapid synthesis and testing of large libraries of compounds. The goal is to develop more potent and safer drugs through these computational and high-throughput methods.
Drug discovery
Drug discovery involves identifying candidate medications through screening chemical libraries, natural products, or virtual screening. It is a lengthy and expensive process to bring a new drug to market. Traditionally, drugs were discovered from plants or microbes, and modern techniques involve high-throughput screening of large compound libraries against biological targets of interest. Hits are then optimized for properties like potency, selectivity, stability, and bioavailability. Once a lead compound is identified, drug development studies are conducted prior to clinical trials to seek regulatory approval. Natural products continue to provide useful structures for drug design despite advances in synthesis and screening methods.
Bioinformatics role in Pharmaceutical industries
Bioinformatics plays a key role in the pharmaceutical industry by enabling target identification of diseases, rational drug design, compound refinement, and other processes. It facilitates identifying target diseases and compounds, detecting molecular bases of diseases, designing drugs, refining compounds, and testing drug solubility and effects. Bioinformatics supports various stages of drug development including formulation, crystallization determination, polymer modeling, and testing before human use. Its integration into the pharmaceutical industry supports drug discovery, healthcare advances, and realizing the promises of projects like the Human Genome Project.
Session 1 part 3
The drug discovery process involves several steps:
1) Hits from high-throughput screening are identified, which may have many potential scaffolds.
2) Hit-to-lead involves synthesizing many compounds to determine structure-activity relationships and improve properties.
3) Lead optimization aims to increase potency, selectivity, and in vivo efficacy while maintaining favorable properties. Efficient synthesis and parallel chemistry methods are important throughout the process.
Introduction to pre clinical screening of drugs
Various Techniques and Methods for screening of new chemical entities in preclinical aspects (both invitro & invivo) for effective and safe clinical usage.
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Bioinformatica 15-12-2011-t9-t10-bio cheminformatics
- 2. FBW 15-12-2011 Wim Van Criekinge
- 7. Example: Agro Known “lethal” genes from worm, drosphila Sequence Genome Filter for drugability”, tractibility & novelty
- 8. Example: Extremophiles Known lipases Filter for “workable”lipases at 90 º C Sequence Genome Functional Foods Convert Highly Energetic Monosaccharides to Dextrane Look for species with interesting phenotypes Clone and produce in large quantities Washing Powder additives
- 10. Drug Discovery: Design new drugs by computer ? Problem: pipeline cost rise linear, NCE steady Money: bypassing difficult, work on attrition Every step requires specific computational tools
- 20. “ Optimal” drug target Predict side effect Where is optimal drug target ? How to correct disease state Side effects ?
- 27. G enome-wide RNA i RNAI vector bacteria producing ds RNA for each of the 20.000 genes proprietary nematode responding to RNA i 20.000 responses 20.000 genes insert library
- 30. Normal insulin signaling Reduced insulin signaling fat storage LOW fat storage HIGH Type-II Diabetes
- 34. Molecular functions of 26 383 human genes Structural Genomics
- 36. Lipinsky for the target ? Database of all “drugable” human genes
- 37. Drug Discovery: Design new drugs by computer ?
- 38. screening - the automated examination and testing of libraries of synthetic and/or organic compounds and extracts to identify potential drug leads, based on the compound's binding affinity for a target molecule. screening library - a large collection of compounds with different chemical properties or shapes, generated either by combinatorial chemistry or some other process or by collecting samples with interesting biological properties. High Throughput Screening : Quick and Dirty… from 5000 compounds per day Drug Discovery: Screening definitions
- 40. Drug Discovery: HTS – The Wet Lab Roboti c arm Read-out Fluorescence / luminescence D istribution 96 / 384 wells Optical Bank for stability
- 42. Drug Discovery HIT LEAD
- 48. Drug-like-ness (Celebrex) Methyl in this position makes it a weaker cox-2 inhibitor, but site of metabolic oxidation and ensures an acceptable clearance
- 49. To assist combinatorial chemistry, buy specific compunds
- 56. Drug Discovery Toxigenomics Metabogenomics
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- 62. Hapmap
- 63. Pharmacogenomics Predictive/preventive – systems biology
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Editor's Notes
- I have the pleasure to update you on our RNAi HTC strategy. First I will give an overview of the different cloning techniques we tried and finally the one we came up with to clone the whole C. elegans genome. Ann Lissens will focus on the RNAi screen.