Pharmaceutical drug discovery is undergoing such rapid innovation that therapeutic breakthroughs that could only once be imagined, are now commonplace in research labs around the world.
With this remarkable success comes further aspiration for the discovery of many more therapeutic pathways and effective new medicines, to give fresh hope to patients. But what challenges will we need to overcome to continue to move forward – and what can we hope to achieve in the future?
To get a glimpse into what this might look like, we’ve enlisted the help of Melanie Leveridge, Head of Screening, Profiling and Mechanistic Biology at GlaxoSmithKline, UK. Below Mel shares her professional insights into what she thinks will shape the future of drug discovery, including the importance of reducing drug candidate attrition, encouraging collaboration, and adopting novel technologies to drive research success.
How can we continue to drive innovation and reduce drug attrition?
The field of drug discovery has benefited from exciting innovation and progress in research, however, there are still some barriers to overcome to ensure the field continues to advance.
Mel highlights that attrition of drug candidates is one of the key challenges facing researchers, both now and in the future. “We need to reduce attrition by increasing confidence that we are selecting the right targets early on, and then understanding how to effectively translate those targets into high quality medicines that address unmet medical needs for patients,” says Mel. “We need to do all this whilst also reducing cycle times,” she adds.
Continuing to support and develop collaboration throughout drug discovery research will also help overcome these challenges, as Mel notes that collaboration is critical to success. “Realistically, no one organisation has all the scientific knowledge it needs internally to select and validate the best targets” she remarks. “Open innovation models and collaborative working between academia, pharma, and technology development companies are key to achieving success.”
Mel predicts that the current collaborative culture will continue to flourish among the whole community, and in turn enhance research innovation. “Currently, the scientific community is a highly collaborative one – and I think that will remain the case well into the future. This will ensure we can continue to drive innovation in drug discovery, which excitingly is unlikely to slow down.”
What key technology developments will enhance drug discovery?
Given the high rate of innovation in drug discovery, many of the novel technologies currently emerging are likely to have a huge impact on research operations in the future. “As an example, high content imaging and phenotypic screening were considered emerging areas only seven or eight years ago, and now they are embedded in discovery research,” highlights Mel.
But even with all these remarkable advancements, Mel is keen to emphasise that it is important not to become complacent. “Technologies are continually evolving and we need to continue to drive innovation, both to continuously improve existing capabilities, and to develop new techniques and methods that can be impactful in the future.” she remarks.
Mel predicts that two areas of technology development will have an immense impact on the way we conduct early drug discovery in the future. The first is the development of technologies that allow us to more readily access patient samples, or more human disease-relevant samples early in discovery. “For example, the development of technologies for miniaturisation of assays will be crucial, because they will enable us to do more with less of those precious patient samples,” she says.
The second area relates to the rapid development of capabilities within big data analytics and predictive modelling. “I think the power of predictive modelling and virtual screening will enable us to identify an optimal molecule in far fewer chemistry iterations in the future” Mel predicts.
She also points out that through these developments, drug discovery scientists will be able to really exploit the power of high content biological assays. “We will have the computing power to analyse data sets much more rapidly, and machine learning algorithms will be able to spot patterns that the human eye can’t,” she predicts. “There is no doubt about it – continuing to develop and implement novel technologies will transform the way that drug discovery research operates in the future.”
What are Mel’s key aspirations for the future of drug discovery?
Looking ahead to the future is a key aspect of Mel’s role at GSK. Not only is it important for her to optimise her team’s research operations and outcomes, but she keeps a broad outlook across the entire field to identify general areas for improvement. As such, Mel shares her three key aspirations, that she would love to see happening over the next five to ten years in drug discovery:
Development of miniaturisation and single cell technologies“These technologies can help us move in a direction where we could screen directly with patient samples (cells/tissues) at scale for every early discovery project,” she says. “This would be fantastic as it would enable us to test whether our molecules are effective at modifying disease states from the very beginning, in the system we really need them to work in, rather than in a surrogate cellular system.”
Selecting the right targets every time
“Wouldn’t it be great if we could select the right targets with absolute certainty every time?” Mel asks. While admitting this is unrealistic due to the unpredictable nature of science, she points out that novel technologies and collaboration could still help us to move closer towards this ambitious goal. “Developments in precise genome editing and our ability to develop complex cellular models that mimic disease, as well as collaboration and open innovation in the target validation area, offer us lots of opportunities to build confidence in the genetic and biological validation of targets in the future,” she remarks
Unlimited computing power
Mel’s third and final aspiration is simple, yet potentially hugely impactful. “In a world where resource were no object, I would like unlimited computing power, so that we can really unleash the opportunity that big data analytics and predictive modelling brings,” she says. “I think this will be an area of rapid growth and development in the coming years.”