Healthcare incentives, price transparency, patent length, and the interaction between medical needs and regulatory processes all need to be re-examined. While there is lots of disagreement, the industry seems to agree on one thing: The system is broken and isn’t serving patients as well as it could be. But how can we fix it?
The President’s signing of the FDA Modernization Act 2.0 into law is a huge step in the right direction for the pharmaceutical industry. The first step in a long-needed course correction, this legislation brings the industry forward – ending decades of unchallenged legislation hampering drug development and no longer serving patients’ needs.
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Per the legislation, the Food and Drug Administration (FDA) will no longer require animal testing on drugs in development. Non-animal drug testing methods (tech beyond mice) will be considered valid after 80+ years of animal testing requirements long predating current technologies like artificial intelligence (AI) and organs-on-a-chip that tested drugs on animals for illnesses they couldn’t even in some cases contract themselves (as indicated by PETA). While this transition from chemistry to biology was slower than it should have been, it will now help bring down the cost and time of drug discovery and get new drugs to patients sooner.
AI, a better mousetrap to predict drug safety
Drug development fails 90% of the time, often for safety, and we all pay for the failures. Medical innovation isn’t getting to the benefits fast enough. The legislative impacts from the FDA Modernization Act 2.0 will help here as predictive models based on mice were good at predicting lethal doses of drugs, but not as good at predicting side effects. Human tissues, coupled with AI that can deal with terabytes of data will blow mice models out of the water. With animal testing requirements finally removed, the pharma industry and its constituents can hope for faster innovation.
So, what’s next? Human liver cells are better at predicting drug toxicity than anything we’ve seen before (including animals and other technological advances). Being able to test multiple organ models on a chip accurately and quickly will lead to predictors of drug efficacy. In fact, the first AI-derived drug candidate, which we hope one day will be approved, is already in development.
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If the models that screen for safety can start to screen out losers early on and drugs could even be successful 50% of the time (versus 10%), it would make a huge impact on the costs of research and ultimately, the cost of drugs themselves. As Prof. Robert Langer, co-founder of Moderna and former Chair of the FDA’s Science Board, noted, “We are at the tipping point of the modernization of drug discovery. Predicting clinical safety is of huge value to pharmaceutical companies and the health of society at large. AI-based prediction of clinical safety of drug candidates does seem to be a very big opportunity. I’ve had similar ideas in other areas of chemistry, where you can use AI to make these predictions. It certainly won’t replace testing, but it narrows the possibilities, and my view is it would speed things up tremendously.”
Not all drugs are the same; And their approval processes shouldn’t be either
The ability for a drug to be approved without multiple years of studies is something that has not previously existed. Beyond cost concerns, the traditional approval process for drug development, which has a lengthy approvals process mandated by Congress and the FDA involving preclinical animal studies, phase 1-3 clinical trials, post-approval phase 4, and two well-controlled medical studies, can mean some lifesaving drugs are held up because of outdated legislative requirements. Unfortunately, many patients do not have years to spare. The wait can come with extremely high costs for those in critical need.
While the continued importance of drug safety is unquestionable, some drugs can be fast-tracked to ensure patient needs are being met. The interaction between medical needs and regulatory processes is being rethought. Congress and the FDA need to ensure that this legislation reflects the needs of patients and the technology that is currently available. The last thing we want to do is punish the pharma industry, or those relying on new drugs and treatments, for success.
Achieving two objectives in tandem: Patent extension & faster returns for drug developers
Imagine you develop a cure for cancer and are rewarded with a patent. A patent essentially allows for a decade of monopoly on the product during which time you can sell it at any price before generic and alternative options become available and the drug is sold at a lower price once approved. If it takes 12-14 years for a drug to be approved, and to benefit from the invention, a company only has 6-7 years to recover its investment.
If we can reduce the failure rate of drugs and reduce the time to approval, giving companies 15 years to recover their investment, the costs of drugs would be significantly reduced. Patent expiry is fixed and extended by law. If a drug company could start marketing a drug earlier, instead of waiting 12-14 years to benefit from an invention, they could do so in 8-10. Having more confidence and clarity on safety and pricing before they decide to go into clinical trials will provide the agility the pharma industry needs to better serve patient needs.
Future forecast: AI as the clear path
The industry is in a state of flux, but the path forward is becoming clear. AI coupled with interconnected human organ systems on chips in place of mice will help solve many of the industries’ long-standing restraints in the years ahead. The future is not only predicting which drugs will work safely on the human body, getting them to market faster and cutting the costs of production but also better-tailoring drugs to patients’ individual needs.
Photo: metamorworks, Getty Images
Isaac Bentwich, MD, is the founder and CEO of Quris-AI, where he and his team are using a bioAI approach to disrupt the drug development process. Prior to Quris-AI, Isaac founded and led three bioAI technology companies, each of which led revolutions in medicine, genomics, agriculture, and conservation.
