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General overview about the history of computers in
pharmaceutical research and development.

Computers are very important in pharmaceutical research and development that
it may be hard to imagine a time when there were no computers to assist the
medicinal chemist or biologist.

A quarter-century ago, the notion of a computer on the desk of every scientist
and company manager was not even contemplated.

Now, computers are absolutely essential for generating, managing, and
transmitting information.


Germination: the 1960s

In 1960 essentially 100% of the computational chemists were in academia, not

in 1962 the Quantum Chemistry Program Exchange (QCPE) can into picture.
Competitive scientists were initially slow to give away programs they worked
so hard to write, but gradually the depositions to QCPE increased.

QCPE proved instrumental in advancing the field of computational chemistry
including that at pharmaceutical companies.

Back in the 1960s and 1970s, there were no software companies catering to the
computational chemistry market, so QCPE was the main resource for the entire

As the name implies, QCPE was initially used for exchanging subroutines and
programs for approximate electronic structure calculations.

But QCPE evolved to encompass programs for molecular mechanics and a wide
range of calculations on molecules.

Gaining a foothold: the 1970s

Some of the companies that first got into using the softwares dropped out after
a few years (but returned later), either for lack of management support or
because the technology was not intellectually satisfying to the scientist
involved. Other companies, like Lilly, persisted.

Other companies such as Merck and Smith Kline and French (using the old
name) entered the field a few years later.


Regarding hardware of the 1970s, pharmaceutical companies invested money
from the sale of their products to buy better and better mainframes.

Two new computer-based resources were launched in the 1970s. One was the
Cambridge Structural Database (CSD) [55], and the other was the Protein Data
Bank (PDB).


The growth:- in 1980s,

This was the growth period and the renaissance period of the computers in
pharmaceutical industries.

Professor Allinger launched his journal of computational chemistry which
includes quantum chemistry , molecular mechanics, molecular simulation ,
QSAR and molecular graphics.

• Development of the VAX by Digital Equipment Corporation (DEC),
personal computer (PC) by IBM and Apple Macintosh brought interactive
computing to new level.

• Communication was faster with electronic mail. Chemdraw and
computers graphics helped researchers in exploring chemical structures.

• Program’s called MACCS was used to check whether a compound had
previously been synthesized and REACCS , for chemical reactions.

• Different softwares for optimizing the geometry of molecules ,for the
lipophilicity of the organic molecules, for predicting the toxicity of a
molecule have been developed.

• SAS , a comprehensive data management and statistical program was
developed for handling the clinical data and for graphical presentation of
multidimensional numerical data.

• The computational chemists used most frequently molecular graphics and
molecular mechanics for drug development.

• Koga of Japan was first to use QSAR to discover the antibacterial agent
norfloxacin around 1982.

• Demand for computer power appeared necessary when free energy
permutation (FEP) theory appeared on the scene.



Fruition:-In 1990s,

• Super computers (Cray 2S) helped in speeding the identification of new
drug candidates, for performing longer molecular dynamics simulation
and quantum mechanical calculations on large molecules.

• Later, Computational technique such as QSAR or data mining was more
effective at discovering and optimizing new lead compounds ,than the

• However , VAX cluster remained as essential part of the technology
infrastructure best suited for management of the corporate library of

• An electronic bulletin board called the Computational Chemistry List
(CCL) has been launched in 1991 which has revolutionized research in
computational chemistry.

• MDL came out with a new embodiment of its compound management
software called ISIS (Integrated Scientific Information System), which
gave researchers exceptional new tools for drug discovery when
similarity searching came.

• Chemical structures could be stored as a series of on-off flags (“keys”)
indicating the presence or absence of specific atoms or combinatios of
atoms and/or bonds which can be quantified in terms of percentage
similarity between compounds.

Drug discovery and development was started to use:

1. Technique based Ex: Programs based on force fields or on statistical

2. Algorithm in which the 3D structure of the target receptor is known or

Three methodologies came into increased usage which benefits the 3D structure
of the target receptor:

• Docking which lets an algorithm to fit a ligand structure into a receptor.
• A computer algorithm to construct a ligand de novo inside a receptor

• Virtual screening would screen hypothetical ligand structures against the

3D structure of a receptor in order to find those most likely to fit and
therefore worthy of synthesis and experimentation.


New computer controlled robotic machinery would permit synthesis of
compounds much more economically than the traditional one-compound-at-a-
time process of medicinal chemistry and automate the biological screening and
reduce the cost per assay.

Hence the improved computer based methods led to faster screening of many
molecules and helped in the discovery of the following drugs:


Generic Name Brand Name Year approved Discovery Activity
in US assisted by

Norfloxacin Noroxin 1983 QSAR Antibacterial
Losartan Cozaar 1994 CADD Antihypertensive
Dorzolamide Truspot 1995 CADD/SBDD Antiglaucoma
Ritonavir Norvir 1996 CADD Antiviral
Donepezil Aricept 1997 QSAR Anti-Alzheimer’s
Imatinib Gleevee 2001 SBDD Antoneoplastic
Ximelegatran Exanta 2004 SBDD Anticoagulant