I had the great pleasure of participating a special seminar arranged by Kasve Ltd and enjoying inspiring presentations on Welfare in the future (in Finnish). Development of drugs and other therapies plays a major role in our welfare. How will drug development change in the future?
Some of the major factors driving change in the pharmaceutical development are patient centricity, ageing (and obesing) population, the economic burden of healthcare, and “big data”, which I’d rather call data explosion: The exponential growth of the amount of relevant data that try to tell us something. Data in healthcare systems and scientific articles, personal genetic data, data collected with wearable devices and by biohackers, more or less subjective patient data collected and shared in the Internet, etc. Ultra-dimensional stuff that doesn’t fit the statistical methods this industry and authorities are used to.
We are increasingly aware and demanding when it comes to our health. Patients search the Internet for scientific and, well, less scientific information. They discuss symptoms online with peers and compare benefits of therapies at sites like PatientsLikeMe.com. They have their genomes sequenced. When they visit their physician they refuse to be just part of statistics; they already know if the common drug only helps 30% of their kind of patients, and they know of clinical studies suggesting a much better efficacy with a novel drug. Desperate patients even demand access to drugs-in-development with little if any solid efficacy evidence.
Unfortunately novel drugs are very expensive. Pharmaceutical companies justify high prices with high development costs due to slow and expensive development because of tough regulations. The authorities justify the tight regulations by protection of patients from the greedy pharmaceutical industry. Whatever the truth, even the richest countries worry about the cost of healthcare with aging populations. Authorities and reimbursement will need to consider the health economics of drugs in addition to safety and efficacy. A cancer therapy adding a month of survival benefit without improved quality-of-life over a cheap medicine will not be considered worth €100,000. We need breakthrough therapies instead of small incremental improvements that just add to the mounting costs.
Breakthrough therapies such as targeted biologicals based on industry-academia collaborations toward a deeper understanding of disease mechanisms could be very efficacious. The downside may however be a smaller patient population, e.g. patients with a specific gene. And again a high development costs would justify an even higher price per patient. Drug development must become more agile.
In the future the line between clinical studies and routine treatments will begin to fade away. Breakthrough treatments especially for rare, life-threatening diseases will be made available to patients based on a shorter development time but subject to continued careful evaluation after the initial approval. This reduces development costs by enabling early market entry; the drug price will also be lower until more data cumulates to justify a higher pricing. Most importantly, patients will be kept well informed on the available data, risks, and alternative therapies. We must have the right to choose between a conventional, low-risk therapy and a breakthrough with high risks due to much shorter evaluation of safety in practice. Approvals and pricing will no longer be so black-and-white; they will be adjusted flexibly based on cumulating data. Pricing/reimbursement will also be cut if practical clinical data suggest a smaller benefit.
This could already be a reality in countries where high-quality general healthcare and comprehensive patient information systems enable follow-up of basically any selected volunteers. The resulting data will of course be very diverse compared to the conventional clinical studies where every single patient visit is strictly controlled and data point is absolutely certainly correct (=very expensive). On the other hand: The resulting data will come from the real world, not only from a controlled study whose setup is optimized to justify the highest possible price. We just need to accept more intelligent ways to analyze data from multiple sources of diverse credibility.
This adds one more factor: Artificial Intelligence is breaking through in healthcare. IBM’s Watson is already a valuable tool for instance in diagnosing rare diseases. Iris AI leverages published scientific data in novel ways, which could help identify better therapeutics. Artificial Intelligence can help analyze large amounts of diverse data. These and other current applications are just a prelude to Artificial Superintelligence, which is estimated by about 2060. Depending on the whose opinion you ask it will either cure all diseases or see humans as mere molecules for which it might also have some better use.
In either case, there will be billions of patients with unmet clinical needs to be treated before 2060. So we’d better roll our sleeves now to develop more innovative therapies with favorable health economics.
Herantis develops two innovative therapeutics aiming at a breakthrough in an unmet clinical need: Lymfactin® for the treatment of breast cancer associated lymphedema, and CDNF for the treatment of Parkinson’s disease.