Omes and omics

Systems biology has had a huge impact on the drug discovery process. But do scientists agree on what this relatively new biological study field comprises? And what impact do the new capabilities in genomics and proteomics have on the pharmaceutical industry? NGP asked Gentronix’ Dr. Steve Beasley and Logopharm’s Uwe Schulte.

NGP. What is the impact of systems biology (proteomics, genomics) and modern assays on drug discovery?
US. Genomics and proteomics have broadened the view on the true complexity of living systems and provided the first tools for approaching it. This has had a big impact on the drug discovery process. With the completion of eukaryotic genomes, the understanding of drug target IP and its value has changed. And rather than identifying and addressing individual targets, more systematic strategies involving whole target families and pathways have become state-of-the-art. Modern proteomics has enforced the concept that drug targets are actually complex functional units that are part of extensive pathways and cellular networks. Drug discovery has become much more systematic, with strong enhancement of throughput and speed, but also at the price of increased investments in early phase development and enabling technologies.

SB. The impact of ‘systems biology’ will probably not be fully realised for some time yet since a key part of delivering the promise of this field will be understanding what systems biology actually is. While it is clear that the scalability of ‘omics’ has been impressively demonstrated, the resultant data tsunami is still far from being rationalised.

From a drug discovery perspective there are two critical areas where this information is needed; the identification and understanding of new tractable drug targets and understanding why drugs do things we don’t want them to. Both have complex multi-factorial issues and both require increasing emphasis on ‘smart’ biological screening approaches to achieve successful progression in drug discovery whilst reducing the attrition rate.

NGP. Biomarker trials require new competencies in design, data analysis and ultimately commercialisation. Are new capabilities in genomics and proteomics making biomarker-based development more feasible for the pharmaceutical industry?
SB. Biomarkers have become a central component in the pharmaceutical development and commercialisation process, and there are two principle areas where this is having impact: clinical trial design and theranostics.

Historically, some clinical candidates have failed to progress not because the drug was inactive but because it failed to reach statistically significant endpoints in a sub-population of the overall study group. Developments in biomarkers have enabled detailed analysis of clinical trial data post study to identify non-responders and increasingly to profile candidates for inclusion within a particular study thus reducing the number of ‘failed’ trials.

US. Biomarkers pose ultimate analytical challenges with respect to complexity, concentration range and individual variability. Their analysis would hardly be possible without the new ‘omics’ developments: breakthrough technologies like mass spectrometry and DNA arrays have provided the basis for comprehensive identification of genetic and proteomic markers, and metabolomic analysis has recently emerged as a complementary approach. All these are dependent on powerful bioinformatic tools that extract and quantitate complex signal patterns from the large amount of data. Still, biomarker analysis is a rather young discipline and requires further improvement in speed, robustness and costs for broad application in the clinic.

NGP. How can high failure rates going from in vitro to in vivo or man be overcome?
US. Failure rates are still surprisingly high, given the potential losses and the huge investments made in technologies to avoid them. Although excessive preclinical testing has reduced problems with toxicity and bioavailability, the lack of efficacy has remained a major risk. Obviously, the currently used assays and animal models are poor correlates of human physiology. One may argue that this is inherent to these systems, but I think that it rather reflects the way these assays and models are designed. Often, target function in complex biological systems is incompletely understood or the role of the molecular environment and side pathways are neglected.

Moreover, compound screening and testing is optimised for throughput and standardised readouts, less for being physiologically meaningful.

SB. There is no one reason why progression rates are as they are, however, there is increasing evidence to suggest that we understand the problems better. Part of the solution will come from better discovery process design and the advantages of parallel screening for biological activity and compound liability (selectivity, ADME and Toxicology). There are critical factors that need to be addressed so that information derived in screening can be integrated into the discovery process to make better molecules: data processing and communication times need to be within the timescales that allow a chemist to incorporate the information into the design of the next set of molecules, and there need to be liability screens available that can be used early in the discovery process to give alerts on potentially hazardous chemical space.  

NGP. Physiological targets are protein complexes rather than individual proteins. What implications does this have on the discovery process?
SB. The impact of computational and post genomic technologies on our understanding of the drug target environment has been enormous. We have accelerated rapidly from a point where we knew little of the target and were restricted to traditional SAR approaches 20 years ago to where having detailed active site structural information is considered routine. We are now beginning to understand some of the subtleties of protein complex formation and the role it plays in drug target interaction, aided in large part by initiatives such as the Center for Molecular and Cellular Systems, who have developed an integrated analysis pipeline that combines complementary isolation approaches with mass spectrometry (MS) and computational tools for identifying protein complexes. As we understand more about the ways in which proteins associate, new target opportunities are being presented that will drive the next generation of drug discovery.

US. Although this concept could have major consequences for drug development, it has so far been only hesitantly implemented by the pharma industry. For example, targets are still defined as genes, and based on this are assumed to be limited to 2000-3000. Understanding targets as protein complexes forming novel interaction structures, this limit is likely a dramatic underestimate. Several important target properties are influenced by associated proteins: complexes form in a cell-type specific way and also determine functional specificity in vivo (i.e. coupling to biochemical pathways). Associated proteins often act as functional modulators and can change the pharmacological target profile. These properties could be exploited to develop drugs with improved specificity and new modes of action.

NGP. What are the contributions of novel technologies to drug specificity and safety issues?
US. Currently, drug safety is a major concern dominating decisions – often to the disadvantage of development of new targets or drug candidates. Thus, increasing drug specificity and safety may be regarded as the key indicator for success of novel technologies. In my view, genomics and proteomics technologies could contribute in several ways. Targeting cell-type or functionally specific protein complexes is expected to result in fewer side effects, and compounds with new modes of action might show less selectivity problems than complete blockers. Another aspect is the ability of target families and networks for systematic and broad (counter)screening.

SB. There are many technologies being developed to address various problems in drug discovery and development. In asking what contribution they will make to drug specificity and safety one needs to be clear where in the process such issues arise and whether a more integrated approach would yield drug candidates that are more specific and safer than currently achieved, and then design in the appropriate solutions to strengthen the process. A fundamental concern is that with the volume of data now separately generated on any given candidate, unless there is a data structure to deliver all the information at the same time, the value of deriving the data in the first place is diminished or lost. A potential solution to this issue comes from the multiplexing of assays to derive a range of outputs from a single experiment.

Uwe Schulte is the co-founder and Managing Director of Logopharm, a German biotech company focusing on membrane target characterisation. As head of Complexio, a biotech start-up, he led the transition into Logopharm as a specialised R&D service provider with independent target development projects.

Dr. Steve Beasley has over 25 years of experience in the pharmaceutical and chemical industry in both major international R&D companies and specialist biotech. He was COO at Cambridge based De Novo Pharmaceuticals, CEO of knowledge base organisation bioKneX and is currently Commercial Director of Gentronix Ltd, responsible for the commercialisation of novel cell based genotoxicity screening assays.