Drug target validation: an interview with Ian Waddell (Charles River Laboratories)
We spoke to Ian Waddell, Executive Director of Biology at Charles River Laboratories, to find out more about the validation of drug targets in his research.
Please can you introduce yourself and tell us a bit about your institution?
My name is Ian Waddell and I am the Executive Director of Biology at Charles River Laboratories (CRL), based at Chesterford Park just outside Cambridge (UK). I joined CRL 4 months ago from the Cancer Research UK (CRUK) Manchester Institute, where I had been Head of Biology in the drug discovery team for 6 years. Prior to that I spent 20 years at AstraZeneca, where my last role was as the Director of Discovery Medicine in the Oncology iMED. At CRL I head up a team of approximately 190 highly experienced biologists, split over 4 sites; Chesterford Park, Harlow, Canterbury and Leiden.
Is there an area of research that you’re particularly excited about at the moment?
Following my experience at the CRUK Manchester Institute, what I am most passionate about at the moment is actually target validation. Whilst at the institute, I witnessed a full range of experiences from unrepeatable literature experiments through to beautifully validated hypotheses that allowed us to move into full drug discovery quickly and efficiently. Way back in the early 1990s, as a new recruit, the very first project I worked on in an industry setting was the β3-adrenoreceptor. The project was very advanced and we had very potent, very selective compounds that worked well in an appropriate in vivo disease model. The only issue is that the β3-adrenoreceptor is not expressed to any meaningful level in adult humans but it took us quite a while to work that one out. That situation is almost unimaginable now, but it represents a lesson that you learn only once and that was really what kicked off my interest in real target validation.
Can you tell us about target validation at Charles River? What techniques do you use and how do you generally go about validating drug targets?
We use the full remit of target validation techniques from siRNA, shRNA, antibodies and tool compounds, through to the CRISPR/Cas9 gene editing system. The key thing to remember is that all of those systems have their faults and the most important thing is to not rely on any one technique.
It is impossible to pick a single target validation technique that works ‘best’ because each target is different – not only in concept, but often in the tools that are available to test your hypothesis. You could argue that from a small molecule drug discovery perspective, a potent selective small molecule is the best validation tool. However, these are very rarely available at the outset and a high quality antibody or an siRNA pool might work just as well. The most important thing, as far as I am concerned, is to always use a combination of different techniques and to select the best reagents possible. Most importantly, when we conduct our target validation work we try to use disease relevant material as much as possible.
What do you think has been the biggest recent development to aid drug target validation?
For me the most exciting change in the field is actually a relatively simple one to say, but not necessarily so easy to do. That is the increasing use of the CRISPR/Cas9 gene editing system to conduct so called “rescue experiments”, where the gene of interest is modified, a phenotype observed and then the same gene re expressed to reverse the observed phenotype.
CRISPR/Cas9 gene editing is advancing target validation in two ways. First, the accuracy that the CRISPR/Cas9 system provides allows us to specifically test our hypothesis, particularly when a mutation or knock-out experiment is required. Second, it allows the ability to carry out rescue or knock in experiments in the same cellular setting that you carried out the mutation experiment.
How do you think the efficiency of drug discovery can improve?
The easy answer would be to say moving ever closer to biomarker driven drug discovery and by that I mean knowing which patients are likely to benefit from a given hypothetical treatment before we even start the drug hunting process. To me that is all about improving our use of informatics in its broadest sense to improve our understanding and interpretation of target validation and target identification. In the not too distant future techniques such as cryo-electron microscopy will revolutionize the way that we conduct drug discovery. The ability to see molecules (large or small) interacting with their molecular target in situ and in real time will allow us a deeper understanding of the interaction, allowing the quicker development of more specific, more potent and more efficacious drugs. The only thing really holding us back at the moment is the cost.
For a personal perspective this really came out of the work that I have been involved within the oncology setting. The Holy Grail is to understand which patients are more likely to benefit from a given treatment before you even begin target validation. In oncology that is often about understanding the cancer specific changes are really driving the disease. Understanding potential patient selection at the start of the process does not make finding a potent, selective compound any easier but it certainly allows you to put in place an assay cascade that truly tests your hypothesis long before the compound reaches the later and more expensive stages of drug discovery.
Where do you think drug discovery is heading in the next 10 years? Are there any exciting approaches or technological advances on the horizon?
In the not too distant future we will become better at continuously monitoring a wide variety of clinical parameters in patients either just before or during clinical trials. Companies such as GoogleX are already using this clinical data to develop new hypothesis.
In my opinion large pharma will continue to contract into leaner, more development focused organizations relying on smaller organizations to deliver them drug candidates. The current trend will continue and increasingly innovation will be driven in small biotechs or from universities. Equally, combination trials will become the norm and the type of modalities used in drug discovery will continue to move away from small molecules towards large molecules.