drug discovery

“Innovations in Bioinformatics - Emerging tools for drug discovery and development”

jorgemata — Wed, 07 May 2008 08:06:08 -0700

Description

The key findings of this report [1] are:

• The bioinformatics market is forecast to grow at a CAGR of 23% to $4.5bn by 2011, from a value of $1.6bn in 2006. The US led the geographical market with a share of 45% in 2006, but Europe’s CAGR of 24.6% will narrow the gap over the forecast period.
• Bioinformatics-enabled protein biomarker discovery will enable the development of safer and more effective drugs, targeted therapies and molecular diagnostics.
• Systems biology modelling is forecast to grow at a rate of 35% over the next five years, the highest growth of any bioinformatics sector. The potential for widespread integration throughout all stages of drug discovery will act as a catalyst for this expansion.
• Knowledge management is currently the leading bioinformatics market segment. This lead will be strengthened by mass adoption of Semantic Web technology and the increasing availability of software through the internet.
• Software for next-generation sequencing has vastly reduced time and cost constraints of DNA-sequencing. The miniaturization of reactions has increased their quality and density, subsequently lowering per-reaction costs.

Biomedical Sciences and Biotechnology

Source

[1] Innovations in Bioinformatics - Emerging tools for drug discovery and development. Business Insights, May 2008. http://www.decisionnewsmedia.com/nl/ARC/osm-0DRN507_2008.asp?c=bgxdtzpqrjkpate

Automation of Crystallization by an Academic Group

Jean-Claude Bradley — Sun, 04 May 2008 08:57:54 -0700

Description

Alastair Florence and colleagues report on the use of an automatic reactor platform from ChemSpeed (1) to accelerate the crystallization of organic molecules (2):

The principal gain over manual crystallization stems from the fact that automation enhances productivity, allowing the search for physical forms to be conducted systematically and reproducibly over a finer grid (e.g. larger solvent library) than might be accessible manually, increasing the probability of observing new forms. In practise, making due time allowance for set-up, sample retrieval and cleaning between experiments, experience has shown that 32 crystallizations per working day is sustainable. Further opportunity for productivity enhancement comes from integration of the platform control PC with an electronic laboratory information management system (LIMS) to provide effective archival, search and retrieval facilities for the recorded control parameters associated with large numbers of crystallizations.

Although High Throughput Synthesis (HTS) has become an integral part of the drug discovery process in companies, larger libraries generally come at a cost to purity and full product characterization.(3) There is still much room available to adopt more automation to the practice of organic chemistry, especially in academic labs. Koppitz and Eis predict (3):

Aside from the technology, we are now entering an era in which chemists working in AMC (Automated Medicinal Chemistry) will probably become more chemistry-oriented than they have been in the past decade, when the focus was on developing and implementing a robust and reliable technology platform. In this context, more chemistry related challenges, such as the discovery and exploitation of new structural motifs in chemical space, development of new chemistries and their application in library synthesis, will hopefully be addressed and solved.

This signal points to more involvement by academia into automating chemistry processes typically done manually. This is significant because there is a greater probability that results will be shared with the scientific community, compared to similar work done in industry.

Eventually it is possible that automation will enable even the open execution of chemistry experiments by leveraging crowdsourcing. (4)

Future of chemistry

Source

1) http://www.chemspeed.com
2) http://www.chemspeed.com/files/publications/sa/pa/2006_crystallization_o...
3) http://www.chemspeed.com/files/publications/sa/pa/2006_Automated%20medic...
4) http://precedings.nature.com/documents/1505/version/1

Robotic laboratories are becoming commonplace, so computational data analysis has to as well

Andrew Walkingshaw — Fri, 02 May 2008 12:29:03 -0700

Description

It's not news that robots are better at routine experiments than postdocs are: Wikipedia points out, on the page on high-throughput screening, that

Automation is an important element in HTS's usefulness. Typically, an integrated robot system consisting of from one or more robots transports assay microplates from station to station for sample and reagent addition, mixing, incubation, and finally readout or detection. An HTS system can usually prepare, incubate, and analyze many plates simultaneously, further speeding the data-collection process. HTS robots currently exist which can test up to 100,000 compounds per day (Hann 2004). The term uHTS or ultra high throughput screening refers (circa 2008) to screening in excess of 100,000 compounds per day.

No scientist can review this many results by hand, but these methods are medically and technologically very important:

High-throughput screening methods have become essential for sifting through large chemical libraries in search of drug candidates, and several sensitive and reliable analytical techniques have been specifically adapted to high-throughput measurements of biocatalytic activity. High-throughput biocatalytic assay platforms thus enable rapid screening.

So to take advantage of the advances in experimental technique, we need advances in informatics to let us deal with this torrent of data.

Future of chemistry

Source

http://nihroadmap.nih.gov/
http://en.wikipedia.org/wiki/High-throughput_screening
http://dx.doi.org/10.1016/j.cbpa.2006.02.033