Dear all,
Almost every biomedical researcher in the world (starting from those who
have the power to use only 1 US dollar to those who have the power to use
20 billion US dollar) have started realizing the importance of
bioinformatics in one form or the other. The public awareness created by
both academicians and industrialists towards a gene-specific or genome
based personalized health care medicine warrants the emergence of a
virtual discipline called Silico Biomedicine. Hence, would it be prudent
to think, "Can SILICO BIOMEDICINE stand as the 21st century beacon? "
Sincerely,
Kangueane
Discussion:
Can SILICO BIOMEDICINE be the 21st century beacon?
Advancements in information technology(1), nanotechnology(2), genomics(3),
proteomics(4), pharmacogenomics(5), and bioinformatics(6) will pave the
way for an information revolution in biomedicine towards a personalized
health care paradigm(7). The recent success of the international
scientific community in decoding the genetic blueprint of the entire human
genome has lead to a post-genomics era, where there is an overarching need
for an intellectual fusion of biomedicine and information technology. The
proposed marriage between biomedicine and information technology in a
productive way is cardinal for knowledge discovery from information
repositories. Bioinformatics plays a crucial role in data manipulation,
data curation and knowledge extraction, thus bridging the gap between
disparate information sources for subsequent model building, refinement
and validation.
The convergence of genomic technology and computational advances are
leading to innovative uses of derived knowledge for rational drug
design(8). Information is the key because life at the molecular level can
be understood as a process in which information is communicated between
cellular compartments and adapted by a balanced process of selection.
Tracing the information flow from gene sequences to cellular compartments
of macroscopic life is fundamentally a problem of describing and modeling
biological information processes. Simulation of molecular processes in
cells using structured mathematical models and subsequent prediction of
drug effects in humans will advance biopharmaceutical research and speed
up clinical trials. For an imaginary patient to benefit from the fruits of
silico biomedicine, it is imperative to tie genome technology with genome
computation(7) and legal regulations(9). The integral components of silico
biomedicine and the underlying disciplines fundamental to its emergence
are clearly illustrated in figure12.jpg (attached), showing its true
inter-disciplinary nature.
>From genomics to combinatorial chemistry, scientific advances are poised
to revolutionize drug discovery(8) and health care. Systematic
quantification of the differences in function as a result of allelic
variation within each of a protein family specific to a tissue or organ or
system will lead to the development of a methodology for generation of a
library of potential drug candidates in silico. The complete mapping of
human genes to their function in the context of diseases, pathogeneses and
immune responses using in silico biomedical models will ultimately result
in the rational identification and administration of individual specific
drug targets. The successful sampling of drug targets from a pool of
chemical/biological entities using computational tools will result in
faster and effective treatment of diseases. Knowledge generated using
bioinformatics tools will serve as input parameters for in silico
biomedical simulation in the context of individual genetic constitution.
Consequently, the derived knowledge bases will help the biomedical
research community in deciphering the finite functional/non-functional
elements of genome in diversified population genetics across the globe in
the 21st century.
References
1. D. Malakoff, Science. 288, 600-601 (2000).
2. J.L. West et al., Curr Opin Biotechnol. 11, 215-217 (2000).
3. S. Firestein, Nature. 404, 552-553 (2000).
4. J.L. Slonczewski, Nature. 403, 478 (2000).
5. W.E. Evans et al., Science. 286, 487-491 (1999).
6. R.B. Altman, Bioinformatics. 14, 549-550 (1998).
7. C. Sander, Science. 287, 1977-1978 (2000).
8. J. Drews, Science. 287, 1960-1964 (2000).
9. J.H. Barton, Science. 287, 1933-1934 (2000
Received on Wed Jun 14 2000 - 11:47:55 PDT
