A meeting of minds: working with academia

pharmafile | November 9, 2007 | Feature | Research and Development, Sales and Marketing |  academia, partnerships, pharma 

The completion of the Human Genome Project created huge optimism that the new information would lead to revolutionary new ways to diagnose, treat and prevent disease. Pharmaceutical and biotech companies were keen to capitalise on this knowledge, believing that the full genome sequence would identify novel drug targets, and genetics would swiftly help validate these targets. Several years on, we are finally beginning to see the real value of genetics in the identification of novel disease-susceptibility genes, disease pathways and the elucidation of gene-gene, gene-environment and epigenetic interactions.

This knowledge will lead to the development of novel diagnostics and personalised therapies through a greater understanding of the underlying mechanisms of disease and the identification of biomarkers and novel therapeutic points of intervention. This success has been driven largely by advances in technology, data handling and analysis, and the increasing dependence on large-scale, academic and academic-industry collaborations.

Academic-industry matchmaking

Academic-industry partnerships can range from multiple industrial partners providing funding for very large projects, to consultancy agreements, or fee-for-service provision by academic groups of simple genetic analyses. Academics may also get involved in partnerships to beta-test new technology platforms within a working laboratory environment or to work more closely alongside industry partners to co-develop new laboratory equipment.

However, within medical genetics, many collaborative research projects centre around the identification of genetic biomarkers of disease or treatment response, or of genes that influence disease onset, progression or response to treatment. To identify genes that influence disease susceptibility or response to treatment often requires whole genome association studies: where the genetic make-up of large numbers of 'cases' (patients with a particular disease or drug reaction) are compared to that of large numbers of 'controls'. Even smaller-scale studies to identify or objectively validate measurable biological indicators of treatment outcome (biomarkers) require access to high-quality clinical data with attached patient histories. These needs mean that the importance of academic-industry partnerships within the field of medical genetics is growing. The success of these partnerships rides on the quality of interaction and mutual respect between team members as well as a shared vision and good project management.

Though many collaborations are born out of individual friendships between industry and academic scientists, it is not always possible to create partnerships in this way. This requirement has led to the establishment of organisations that can help identify the right academic partners for pharmaceutical and biotech companies and manage multi-centre partnerships on their behalf.

What attracts academics?

There are several factors that could increase the attractiveness to an academic of an offer to work in partnership with industry. It is important to academic researchers, for example, that they are fully involved in the discovery and development process, as it is often scientific curiosity that is driving their involvement. Equally, it is valuable for academic researchers to see the applications of their work in the clinic in a way that may not normally be possible. This opportunity to 'look over the fence' can be an appealing prospect for academics.

In addition, an individual researcher's success is judged in academic circles on the rate of quality articles that they publish. The ability to use the results of any collaborative work in their own work for non-commercial purposes is therefore a pre-requisite for most agreements.

But choosing the right partner to work with is critical to the success of any academic-industry partnerships. Companies like to be seen to be working with key opinion leaders. Relevant expertise and access to appropriate data are obvious factors, but personality can also play a major role in shaping any interactions. Some of the most productive partnerships are built up through an initial interaction between a particular scientist within a company and a like-minded scientist from a university. Mutual respect and shared visions greatly aid these working relationships. Often a collaboration stems from an initial suggestion from the company scientist to their senior colleagues within the research and development team. From an initial interaction between these two individuals, a larger collaboration can grow with additional partners brought in by either side. It is not always possible to arrange partnerships using this grass roots approach; and, this is where companies such as London Genetics can play a key facilitating role.

When the drugs don't work

One of the major downfalls of medical pharmacology is that drugs generally do not function to the same degree of efficacy in all patients and may only exert their desired therapeutic effect in 30-70% of patients. A major goal of biotech and pharmaceutical companies is the identification of specific biomarkers for use in disease diagnosis and for predicting disease onset, progression and drug response also known as pharmacogenomics.

These biomarkers are required to better match patients with therapies that will work for them, and could help improve safety of medicines, as those patients who may suffer adverse reactions to a treatment could be screened prior to the prescription of any given medication.

Stratified medicine is anticipated to have a major effect on both clinical practice and the development of new drugs and diagnostics. Historically, stratification of patients has occurred after drug approval. However, the drug development industry could benefit from implementing stratification prospectively, enriching the population of patients entering clinical trials with those patients expected to respond well. This enables the trial sample size that is required to detect significant efficacy to be reduced, which, in turn, could reduce the costs associated with drug discovery.

Medicines that are aimed at sub-groups of patients that exhibit better responses are often associated with companion diagnostics, the cost of which often compensates for the reduced market size. For example, one of the first such drugs is Herceptin (Genentech), a breast cancer treatment that is most effective in patients that have high levels of expression of a receptor tyrosine kinase, HER2/neu, on their tumours. In this case, companion diagnostics that use immunohistochemistry or fluorescence in situ hybridisation to identify the level of HER2 receptors on tumour biopsies have been created by a number of different companies, and Bayer Diagnostics has developed a test that quantifies receptor expression levels from serum.

The use of clinical biomarkers in a safety context is illustrated by the recent change by the FDA to the label of Coumarin, a branded version of warfarin, to encourage healthcare providers to use a genetic test prior to prescribing the blood thinner. A patient's response to the drug can be influenced by which versions they carry of two genes, for the enzymes CYP2C9 and VKORC1.

The tests, which identify five polymorphisms within the CYP2C9 gene and two polymorphisms in VKORC1, could help physicians better determine the best drug dose to administer to individual patients and lower the risk of patients suffering bleeding complications. FDA economists estimate that by formally integrating genetic testing into routine warfarin therapy, the US alone would avoid 85,000 serious bleeding events and 17,000 strokes annually.

The identification of genetic biomarkers for either diagnosis or prediction of treatment response requires access to high-quality patient cohorts with associated clinical data. This information is best acquired through collaboration with clinical-academic centres of excellence.

Companies may also be interested in working with research groups headed by a respected expert in the field to help validate any biomarkers that they have identified, using a different set of clinical samples.

Safety in numbers

Following the Human Genome Project, more than five million single nucleotide polymorphisms (SNPs) were identified by the SNP Consortium. These are regions of the genome where a single base pair within the DNA differs between individuals within a population. The relative distribution of these SNPs throughout the genome in different populations was subsequently mapped by the HapMap project. Together, these projects led to the creation of a database of SNPs that can be used to design whole genome association studies.

The first results of the Wellcome Trust Case Control Consortium were published earlier this year (June 2007). This large, genome-wide association study analysed case:control collections from seven major disease areas using 50,000 SNPs within the genomes of 17,000 individuals. Statistical approaches were used to compare the frequencies of genetic variation in disease cases and in healthy controls from the same population.

As well as confirming the involvement for some genes for which disease association had already been reported, the study identified novel genes that affect susceptibility to rheumatoid arthritis, hypertension, Crohn's disease, coronary artery disease, bipolar disorder and type I and type II diabetes.

Many of the genes identified have only a modest effect (increasing the risk by only 1.2 or 1.5 times), confirming the importance of using appropriately large samples in studies. More and larger studies are likely to be needed to fully understand how each of the genes interacts with the others and also the environment to generate an individual's susceptibility to any particular condition.

The success of whole genome association studies is dependent on access to large cohorts of clinically well-characterised cases and controls. Often these large databases of clinical samples have been assembled over many years by dedicated teams of clinicians and research scientists. As it is both difficult and expensive for companies to gain access to sufficient samples of a high quality to build up their own databases, it makes sense for industry to collaborate with university hospitals to carry out genome-wide association studies. Such collaborations can also tap into the expertise of key opinion leaders in statistics, genetics and the diseases of interest within the hospitals and academic institutions to aid study design.

Genes and adverse reactions

Identifying patients that will experience adverse drug reactions (ADRs) is of great importance to pharmaceutical companies as reports of these reactions could severely limit the use of an otherwise effective drug or, in some cases, cause the withdrawal of a drug from the market. Approximately 10% of new molecular entities face withdrawal or reports of serious ADRs following FDA approval. Type B reactions, which are idiosyncratic reactions that are not necessarily linked to the dose of treatment administered, are rare but there is evidence that susceptibility to at least some of these reactions is under genetic control.

The rarity of these reactions means that their genetic basis is hard to study, as no single European country will generate a sufficient number of cases within a reasonable timeframe to enable genetic analysis. A European collaboration to establish a case-controlled DNA collection for studying the genetic basis of these reactions has now been established. EUDRAGENE collates data from patients across Europe, much of which is collected for regulatory agencies in those countries on a routine basis already.

Patients are invited to complete a short questionnaire including demographic information and medical history, as well as donating a blood sample and providing written consent for the use of both their medical records and the anonymised sample in genetic studies. Data on the drug suspected to be the cause of the ADR and the indication for which this drug was supplied is also stored, along with other information on exposure to other medicines and environmental factors.

The data collected through this collaboration will be freely shared, so long as researchers submit any genotyping data to the main database so that any future research can make use of what has already gone before. This is another example of how industry can benefit from the wealth of data generated through academic partnerships. The importance of this field is underlined by the FDA's formation of a Serious Adverse Events Consortium. The FDA has named 12 industry representatives as 'foundation members'.

Into a golden age of genetics

We are entering a hugely exciting time in genetics as genomic technologies – genotyping, sequencing and comparative genome hybridisation – have all matured. Many believe we are entering another golden age of genetics as these technologies will allow us to finally answer many of the fundamental questions around the biology of diseases.

These include identifying disease-susceptibility genes for common conditions; identifying biomarkers that could be used for disease diagnosis, as indicators of disease status or to predict and monitor response to drug treatment; and identifying genes that could influence whether patients experience adverse reactions to drugs. In addition, the speed and cost of delivering answers is constantly improving, especially as whole-genome sequencing costs fall to thousands (or potentially hundreds) of pounds per genome – in fact, there is currently a race to sequence a genome for as little as $1,000.

Answering many of these questions requires 'big science' -large datasets and extensive analytical computing power – and this is best achieved using a collaborative approach, through a consortium of partners from industry and academic centres of excellence in genetics and genomics. Companies are well placed to set up and manage both these and smaller partnerships to ensure their success.

Nick Lench is chief executive of London Genetics. The company facilitates and manages partnerships between the healthcare industry and London centres of excellence in genetics and genomics-based medical research. For more information visit the company's website: www.londongenetics.co.uk.