An approach that could reduce the chances of drugs failing during the later stages of clinical trials has been demonstrated by a collaboration between the University of Cambridge and pharmaceutical company GlaxoSmithKline (GSK).
This further suggests that human genetics can support the development of new therapies, and can offer insights into their safety profile early in the development process
The technique involves identifying genetic variants that mimic the action of a drug on its intended target and then checking in large patient cohorts whether these variants are associated with risk of other conditions, such as cardiovascular disease.
When developing a new drug for market, pharmaceutical companies must not only demonstrate that it is effective at treating a particular condition, but also that the drug does not have any adverse side-effects in patients. For example, the Food and Drug Administration, which approves all new medicines for use in the USA, has defined that any new anti-diabetic medicines need to demonstrate cardiovascular safety. However, in many cases adverse safety profiles do not become apparent until late in the drug development process, by which point millions – possibly even billions – of pounds will have been invested.
In a study published today in the journal Science Translational Medicine, scientists have provided a proof of concept that it is possible to use genetic analyses to demonstrate systematically at a very early stage whether a drug will alter the risk of developing other conditions.
The University of Luxembourg today announced the publication of a research article in the internationally renowned scientific journal Nature Communications. The article is based on research on the interaction between microorganisms in the gut and the human body through the development of the artificial ‘HuMiX’ model.
HuMiX, ‘Human-Microbial X(cross)-talk’, represents an ‘organ-on-a-chip’ model for the human gastrointestinal tract. The model is developed to study the interaction between the microbiome, the community of all microbial organisms that live in and on our body, and the human host – all in vitro. The model and resulting insights will allow a better understanding of whether changes in the gut’s microbiome cause disease, or if such changes are a consequence of the disease.
The human microbiome is emerging as a key area of research within which HuMiX is the only model able to replicate the community of microorganisms in the gut while also allowing the study of their impact on human cell physiology. This technological breakthrough has not only the potential to change the way patients are given drugs by pre-screening their effects on patient-derived cells and microbiota outside of the body, but also open up a new market segment for HuMiX in clinical drug development.
Focus on increasing throughput of processes has favoured poorer models with lower chances of success
The search for new medicines is becoming unsustainably expensive despite huge technological advances because researchers are using the wrong methods, experts say.
They say drug discovery should focus on ‘validity’ – how well the results of experiments predict results in sick people. Instead, it has focused on methods that are easy to industrialize or methods that are academically fashionable.
In a report published in the journal PLOS ONE, Jack Scannell, from Oxford University’s Centre for the Advancement of Sustainable Medical Innovation, and consultant Jim Bosley approach drug discovery using mathematical tools that are used by economists to study decision making. They show that the chance of discovering an effective drug is surprisingly sensitive to the validity of the experimental methods. Small changes in validity can have a bigger effect than running 10 or even 100 times more experiments.
They argue that productivity has declined because the most predictive methods lead to the discovery of good drugs, and research in those areas stops (e.g., stomach ulcers). This leaves scientists working on as-yet-untreated diseases using less predictive discovery methods (e.g., Alzheimer’s). They also suggest that changing industrial and scientific fashions have contributed to the problem.
The result: Methods have become less predictive over time, worse decisions have been made, and the cost of discovery has gone up.
Drug approvals have increased since 2012. The researchers say that this is likely down to the rising use of genetic information which improves the validity of the methods to discover treatments for rare diseases, though less so for common diseases.
Dr Jack Scannell said: ‘There is a nasty puzzle at the heart of modern biomedical research. On one hand, the technologies that people think are important have become hundreds, thousands, or even billions of times cheaper. On the other hand, it costs nearly 100 times more to bring a drug to market today than it did in 1950. New drugs can be very expensive, yet the industry is closing labs and firing scientists. Our work goes some way towards explaining the puzzle. Governments, companies, and charities should focus on identifying and funding predictive methods, even if they don’t match current scientific fashion.’