A year ago GT devoted its cover story to the question of whether pharma has what it takes to apply systems biology to drug discovery — and make it work. While pharma is willing to try new things, we argued, they might not have the organizational flexibility to create a truly multidisciplinary environment where a systems approach to biology might take root. At the time, pharmas like Eli Lilly and AstraZeneca were creating teams designed to bring biologists and bioinformatics specialists closer together, but it was still unclear whether investing in large-scale efforts to model biological systems would pay off in the form of new drugs, quickly.
In the past year, the evidence suggests that systems biology remains primarily an academic endeavor. In just a sampling of the public sector initiatives involved in systems biology, the National Cancer Institute announced in late October that nine academic groups would share almost $15 million to develop what they called Integrative Cancer Biology Programs, and earlier in the fall the Howard Hughes Medical Institute and the National Institute of Biomedical Imaging and Bioengineering promulgated that they would support up to 10 groups to develop graduate training programs integrating biomedical science with the physical sciences and engineering.
But there are signs that FDA is taking an interest in modeling approaches to predicting the efficacy and safety of new drugs and diagnostic tests. In a white paper published in March called “Innovation or Stagnation — Challenge and Opportunity on the Critical Path to New Medical Products,” FDA cited computer-based predictive models among a number of new methods that should be included in pharma’s new product development toolkit. To startups involved in disease modeling (see “Entelos Takes Step in Drug Development on its Own,” p. 15) this is a sign that systems biology may soon be considered practical.
In its Jan/Feb 2004 issue, GT also wrote about US Genomics, the company once touted as having the next-generation DNA sequencing technology to beat. A year ago, Steve Gullans, a molecular biologist on sabbatical from Harvard, had recently joined US Genomics as chief scientific officer, and the company was searching for the most effective means of applying its technology to amplification-free measurement of protein and RNA levels. Last year, the company launched its instrument and reagent platforms, designed to directly detect and measure the quantities of individual molecules of nucleic acids, microRNA, siRNA, and proteins. In September, Gullans moved on to become president and CEO of RxGen.
Coming up Next Month in GT Don’t miss these features in the March issue: Plant and animal genomics Coming on the heels of the annual Plant and Animal Genome conference, this timely story will look into an area of genomics that tends to get little glory despite its many accomplishments. We’ll introduce you to the most recent developments in model organism genomics research and show how it’s pushing into novel terrain. High-performance computing As most researchers know, integrating biology with computer science involves more than just writing innovative algorithms. Designing the optimal hardware for carrying out biological calculations can determine whether a job lasts one day or six months. We’ll look at the hardware solution du jour, and assess to what degree it makes life easier for computational biologists. MicroRNAs and RNAi One of the latest discoveries to hit the RNAi world is the microRNA, a molecule found in many organisms that acts like an siRNA when targeted by the Dicer enzyme. We’ll discuss how microRNAs are thought to affect gene regulation and what impact they could have on the field of gene silencing.