The document provides an overview of the modern drug discovery process, which involves 5 main steps: 1) Target identification and validation to find the molecular structures involved in the disease. 2) Hit identification and validation to find small molecule leads that have the desired effect on the targets. 3) Moving from a hit to a lead by refining hits into more selective compounds. 4) Lead optimization to improve properties and address any deficiencies while maintaining desired effects. 5) Late lead optimization to further assess safety before clinical trials. Modern drug discovery is an expensive process that can cost over $1 billion on average due to large investments required. Bioinformatics and genomic/proteomic technologies help accelerate the process and reduce

1. UNIT 1
OVERVIEW OF MODERN DRUG
DISCOVERY PROCESS
Presented by Miss. Sweety Gupta M Pharm, pharmacology
BLDEAs SSM COLLEGE OF PHARMACY AND RESEARCH
CENTRE, VIJAYAPUR

2. • Drug discovery is the process by which new
candidate medications are discovered.
• Modern drug discovery is usually a capital-intensive process
that involves large investments by pharmaceutical
industry corporations as well as national governments.
• A "target" is produced within the pharmaceutical industry.
Generally, the "target" is the naturally existing cellular or
molecular structure involved in the pathology of interest
where the drug-in-development is meant to act.

3. • Steps involved in Drug discovery-
• Step 1 – Target identification and Validation-
• Target identification and validation kicks off the whole drug
discovery process. Naturally occurring cellular or modular
structures that appear to play an important role in
pathogenicity or disease progression are normally targets for
therapeutics. A good target needs to be efficacious, safe and be
accessible by the drug molecule/meet clinical needs of the
prospective patient.
• Following identification of the drug target, a systematic
validation approach should be adhered to for the mode of
action of lead candidate to be assessed for efficacy. The
approach itself depends on the therapeutic area, but has a set
of general principles that include disease association, preclinical
evidence in key cells, preclinical evidence in intact systems (i.e.
transgenic animals), and literature survey and competitor
information.

4. • Step 2 – Hit identification and Validation-
• The obvious next step is to identify whether the small molecule
leads have the desired effect against the identified targets.
There are a number of approaches by which hits can be
identified, including high-throughput screening, knowledge-
based approaches, and virtual screening. Validation of hits is
required following initial screening, and again there are a few
options to choose from.
• Step 3 – Moving from a hit to a lead
• After a number of hit series have been established, the aim at
this point is the refinement of each hit series in order to
produce more selective compounds. Multiple series should be
worked on in tandem, as it is likely that some hit series will fail,
often due to particular characteristics of the series. Focusing on
multiple structurally different sets of hit series will help to offset
this possibility.

5. • Step 4 – Lead Optimization
• At this stage, the aim is to maintain the desired properties of lead
compounds while improving on possible deficiencies of their
structures, with a view to produce a preclinical drug candidate. This
stage can be used to find out whether your drug metabolizes in the
right area of the body, or whether there are currently any side effects
that are cause for concern. For this process, an integrated approach is
recommended. The combination of specialists in computational
chemistry, medical chemistry, drug metabolism, and other areas can
provide unique insights into this late stage of the process.
• Step 5 – Late Lead Optimization
• Before progression to preclinical and clinical trials, late stage
optimization, in which further pharmacological safety of a lead
compound is assessed, is a vital step. If this stage is overlooked,
problems in efficacy, pharmacokinetics, and safety are more likely to
occur later on in drug development. Safety optimization is a core
stage, the aims are to identify and progress the leads with the best
overall safety profile, remove the most toxic leads, and establish a
well-characterized hazard and translational risk profile to enable
further in vitro tests.

7. • Economics of Drug discovery-
• The cost of drug development is the full cost of bringing a new
drug (i.e., new chemical entity) to market from drug discovery
through clinical trials to approval. Typically, companies spend
tens to hundreds of millions of U.S. dollars on drug
development.
• A new study in 2020 estimated that the median cost of getting
a new drug into the market was $985 million, and the average
cost was $1.3 billion, which was much lower compared to
previous studies, which have placed the average cost of drug
development as $2.8 billion.

8. • Role of bioinformatics in drug discovery-
• Bio-informatic analysis can not only accelerate drug target
identification and drug candidate screening and refinement, but
also facilitate characterization of side effects and predict drug
resistance.
• The various roles are-
• Drug target identification-
• Mining and warehousing of the human genome sequence using
bioinformatics has helped to define and classify the nucleotide
compositions of those genes, which are responsible for the
coding of target proteins, in addition to identifying new targets
that offer more potential for new drugs

9. • Drug target validation
• Bioinformatics also provides strategies and algorithm to predict
new drug targets and to store and manage available drug target
information. After the discovery of “potential” drug targets,
there is an inappreciable need to establish a strong association
between a putative target and disease of interest.
• Cost reduction
• The current high cost of drug discovery and development is a
major cause for concern among pharmaceutical companies
• Advances in bioinformatics accelerate drug discovery process,
beginning with drug target identification and validation (viz.,
Docking), to assay development, and virtual-high-throughput
screening (v-HTS)—all with the goal of identifying new potential
chemical entities.

10. • Promote novel/new drug development
• Bioinformatics can act as proper interface, and provides new
approaches and opportunities to pharmaceutical companies to
efficiently discover potential drug targets and develop novel
drugs.

11. • Genomic and Proteomic technologies-
• Genomic and Proteomic technologies have been developed
over the last several years. These methods are aimed at:
a) discovering new genes and proteins.
b) quantifying and analyzing gene and protein expression
c) assigning functionality.
Being able to compare levels of gene and protein expression
between diseased and normal cells or cells treated with
compounds, which vary in their efficacy and toxicity, could
prove valuable in:
a) identifying new drug targets.
b) optimizing the choice of lead compound candidates by more
closely predicting their success or failure.

12. • Genomics-
• Study of genes and their function.
• Aims to understand the structure of the genome (mapping of
genes and sequencing the DNA).
• Seeks to exploit the finding from the sequencing of the human
and other genomes to find new drug targets.
• Proteomics-
• Proteomics is essentially protein analysis.
• Could be described as a broad classification for a set of
technology and bioinformatics platforms aimed at the
comprehensive molecular description of the actual protein
complement of a given sample. Presently, it is typically
associated with systems biology. Progress in characterizing rapid
posttranslational protein modifications.

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