6 Predictions for the Next 10 Years of Biotech
Updated: Nov 18, 2020
2018 was the year of the ‘Biohacker’, the year when rogue tech hacking approaches and drop-out founder archetypes collided with the normally cautious, PhD-laden biomedical research community. Biohacking became the in vogue wild west approach to advancing health, medicine, and even the food we eat.
The year was rife with momentous, entertaining, morally questionable, and sometimes just odd headlines: genetically edited babies born in China, self-injecting ‘cures’, meat that’s not meat, and of course, Do-It-Yourself CRISPR kits. Despite the hype, the mentality of move fast and build (rather than break) is settling in and finding it’s place amongst the most difficult of scientific challenges.
As Biohacking grows-up and becomes a more mature and measured version of itself, Bioprogramming, if you will, we can expect a wave of unprecedented changes in how we approach health and medicine.
Here are my predictions for major changes in the medical landscape over the next 10 years.
1. Shift from Small Molecule Blockbusters to Targeted Therapies
It is bold to predict the upheaval of business as usual for a multi-billion in annual revenue, decades-old industry, but the days of the of blockbuster small molecule are waning.
Driving this shift are the forces of lower development costs, lower diagnostic costs, and better pre-clinical drug selection.
Competing therapeutic technologies are coming into their own, shifting the focus towards cell-based therapeutics, hardware interventions, or repurposing of known compounds. This is certain to knock some lustre off the small molecule development path that has high failure rates and typically requires hundreds of millions to develop.
Furthermore, the next generation of therapeutics entering drug pipelines will contain targets selected by AI screening, likely improving the 86% clinical trial failure rates for small molecules.
Decreased expenses in taking a drug to market make smaller target markets more tenable.
Improved disease mapping, continued growth in personalized medicine, a motivated patient population, and cost to market reduction for targeted therapeutics will leave the large blockbuster molecule taking a backseat to targeted therapeutics over the next decade.
2. Cells as Therapeutics: Beyond the CAR-T
By co-opting the T cell’s natural search and response programing, CAR-T cell therapies have become the first living programed ‘smart’ therapeutic.
Immune cells, followed closely by stem cells, are the most motile cells in the human body. A single cell can cover the full breadth of the body in a matter of minutes to hone in on a target site when necessary. Using native cell motility for therapeutic delivery or triggering an immune response means that cells can be reprogrammed for a myriad of therapeutic uses.
Future therapeutics and vaccines may consist of a single injection of living cells that serves as a long-lived universal influenza vaccine or suppression of autoimmune disease
The next decade will see continued development of human cells as therapeutics that yield long-lasting permanent to semi-permanent results.
3. Artificial Intelligence Augmenting Medical Practice
Specialists and non-specialists alike will have to rely more heavily on artificial intelligence generated diagnostics, data gathering, and patient outcome monitoring. To keep pace with shifting technologies this will become a necessity over the next decade.
Imagine being a physician and coalescing all research studies (> 2M scientific articles are published each year), all available secondary information, and then selecting from a slew of therapeutics. Now repeat this for each and every patient.
Mistakes will be made, suboptimal intervention courses will be charted.
AI medical assistants can circumvent this, freeing up time by coalescing information to augment Physician decisions. AI assistants will provide a powerful resource for data management from bench to bedside.
Implementing AI in health care will free up time for medical professionals and will become an important tool for managing patient welfare before, during, and after medical intervention.
4. Human Tissue Engineering: From Better Drug Discovery to Organ and Tissue Transplantation.
The only effective intervention we have for organ failure is transplantation.
Organ failure is brought on by years of damage and even though organ decline can be stayed off temporarily by therapeutic intervention, a failing organ means patients have a few years to months before a replacement is necessary.
Thin a-vascular tissues such as corneas and thin band-aid like skin have made progress. But the holy grail of tissue engineering, engineered vascular organs will begin transplant studies within the next decade.
More immediately relevant is the adoption of 3D tissue use in therapeutics screening.
Currently, animal models act as poor surrogates for testing of human targeted therapeutics. On the way to providing full human organs and tissues small human tissues that act as surrogates for 3D human tissues are poised to yield better drug pipeline candidates through more accurate preclinical testing and screening.
5. Disease Diagnosis and Treatment
The history of medical practice is based on classification of diseases by observable clinical presentations. The next decade will shift away from symptomology and towards true genetic and classifiable etiology. Classifying patients with a genetic test and true biochemical analysis has repeatedly led to sub-classifications of diseases much to the benefit of the patients.
One notable example of this is a household recognizable disease, Diabetes.
Diabetes Mellitus where mellitus means sweet in Greek, a nod to the excess sugar in diabetic urine was recognized over 3,000 years ago. In 1959 two distinct types of diabetes were characterized (Type I and Type II) and in early 2018 a report detailed that Type II Diabetes appears to be 5 distinct diseases, including a late-stage autoimmune version striking people in their thirties. The identification of these subsets was in part due to genetic cluster analysis.
All 6 versions of Diabetes are treated the same, with palliative care, or as we know it daily shots of insulin. But we now know the preventative measures long prescribed, cut out sugar, lose weight are not as relevant for some patient groups as a targeted immunosuppressant.
Over the next decade the medical field will shift away from symptomatology and towards etiological genetic-based diagnosis. Genetic based diagnosis will increase in prevalence as the costs around analysis are driven down.
DNA detection is already possible on a strip of paper. Combine genetic diagnosis with AI analysis of genetic patterns, disease presentation, and clinical outcome data, and look for reduced waste in superfluous treatments, improved outcomes, and an increased interest in targeted therapeutic interventions.
6. Combining Two Titans of Biomedical Research: Neurobiology and Immunology.
When Immunologists and Neurobiologists get together over a beer they often joke about who choose the harder subject for their PhD research. Both fields have decades of research leading down convoluted paths revealing ever more questions and at best complex partial solutions. For starters, over 120 types of immune cells have been described in the human body. Often the only other scientists who are invited into the professional woes conversation over a beer are theoretical physicists.
Difficulty aside, there are a few researchers curious enough to have noticed there is a huge overlap between molecules of the immune system and the nervous system. For example, our immune cells not only respond to serotonin and dopamine but produce it independently of the nervous system.
Control classically defined neurotransmitters to shift autoimmune disease prognosis? Likely, yes.
2019–2029: The Next Decade
Streamlining drug development processes by adopting tech approaches and applying complex data analysis is going to drive significant changes over the next decade of biomedical research.
Cheaper, faster, better, and (of paramount importance in medicine) safer interventions will flood the market. From AI in medicine to cells as long-lived therapeutics the aging baby boomer generation will assist in driving these changes. A large population of people needing therapeutic interventions are about to come online. This population, sometimes called the silver tsunami in healthcare are the experimental baby boomers who redefined american culture in the late 1960s, and they are not about to shy away from creating some waves in healthcare.
Biohacking purists may argue that it started with PCR in the 1980s and 40 years later led to CRISPR. But it’s so much more than just programing or resplicing DNA. The ability to manipulate cells, data, and perhaps the ability to build life itself is now poised to move toward unprecedented mastery over human disease in the next 10 years.