The future of cancer therapeutics (a personal view)



Drug treatment for cancer is expanding at a staggering pace. Not too long ago, we were looking an effective new drug every 2-3 years, and for each new drug that made it to the FDA list, it would be matched by a truckload of failed compounds and negative trials. This contrasts sharply with the current situation where multiple new drugs get approved every year. Cancer is being successfully targeted from every direction and at every level, from intracellular processes to tumour microenvironment to host immunological response. The decades of basic research on cancer is finally paying dividends on an unprecedented scale. In my humble opinion, several important factors have contributed to this success.

  • First, improved understanding of basic cancer biology allows a rationale design of drugs that are much more likely to actually work. This contrasts with the old methods of screening huge panels of random novel synthetic compounds, hoping to find something useful. Instead of trying to find a needle in a haystack, current approaches feature clear targets – a particular cellular pathway, a particular functional protein etc. so that candidate compounds are no longer random, but rational.
  • Secondly, the exponential development of general technology – the use of computer aided designs, simulations, high-throughput laboratory equipment, artificial intelligence, new biotech breakthroughs (such as CRISPR) all factored into the ease, speed and precision with which new treatments can be developed. Whole new treatment modalities have emerged in the new millennium: target therapy, immunotherapy, ADCs, cellular therapy … and likely coming up soon, gene therapy.
  • Thirdly, and perhaps most importantly, the change in our mindset about cancer heterogeneity have revolutionized trial outcome. It is perhaps frightening to imagine how many potentially useful candidate drugs that have been, over the years, wrongfully discarded simply because of a lack of test subject differentiation. Take, for instance, the negative early trials for an EFGR inhibitor tested in an unselected western lung cancer population, and contrast this to the proven 80% efficacy of the same drug in selected EGFR mutant patients. With the advent of patient selection and the identification of predictive markers to allow such selection, success rates of trials have markedly improved, leading to the rapid expansion of approved drugs.

Each of the above three factors have not only made a huge impact in the development of new effective treatments, but each of these three factors is, individually, in rapid development: we are rapidly elucidating the complex interacting cellular pathways in cancer development, maintenance, metastasis and immune evasion; technology is now advancing in leaps and bounds, it would mind-boggling to imagine the upcoming disruptive effects of quantum computing and AI in biotechnology; the unending search of better biomarkers and the streamlining of trial designs will ensure higher success and lower wastage in future clinical trials, and on top of all these, there are newcomers like China with huge patient populations to ensure rapid clinical trial accruals and readouts.

So, the rapid growth of new drugs is set not only to continue but to boom in the near future, which brings us to the next question: how we can make these treatments affordable so as to benefit as many patients as possible?

Cancer development is essentially “natural evolution” on a small scale: every time a treatment is given, it kills off a certain susceptible population of cells leaving resistance clones which survives and then propagates, accumulating more and more resistant phenotypes. Frequently this happens with activation of alternative pathways or acquisition of new mutations. Drawing from other biological models such as treatment of HIV and TB, we learnt that use of correct combinations of drugs targeting different pathways can forestall the emergence of resistance and achieve complete eradication and cure. The use of combinations in cancer treatment is being explored and has been rapidly developing. Combining different modalities have yielded highly effective combinations for many cancer types. This trend is not only destined to continue, but likely to intensify (think triple combinations or more).

However, such approach would only amplify the problem of skyrocketing costs. Not only are patients dealing with payment for a single new expensive drug, but simultaneous combinations of them too! Regardless of whether the patient, the insurance companies, or the government eventually foot the bill, the enormous cost burden ultimately need to be borne by the society, and I find the whole question of long-term sustainability rather troubling. In the context of a global economy ravaged by a pandemic, diminished by trade wars, and threatened by inflation, weakened by an aging population, sustainable costs of medical treatment must be an ever important consideration. There is probably no single or simple solution to this, but my thoughts include potential strategies to lower the costs of R&D and increasing efficiency of clinical trials (and hence final product pricing):

  • Monopoly is bad for the market and the pricing, but on the other spectrum, excessive competition is also detrimental. Take for example ALK inhibitors that are effective in a small (3-5%) subset of lung cancers: there are currently at least several on the market with similar mode of action. Each pharmaceutical company needs to invest similar amount of resources in their respective development, but would the crowded market dilute the sale quantities and hence the ability to lower prices?  Striking a healthy balance between excessive vs. insufficient market competition may lead to a greater economy – could more collaborative efforts (short of mergers) between pharmaceutical or biotech companies to pool resources lower the costs?
  • Close communication between clinicians and scientists is essential to optimize best use of resource by guiding research into areas of greatest need. Insightful planning of clinical trials is paramount to eventual success of a drug product – the agonizing choice between restricting recruitment to highly selected cases versus broadening the recruitment criteria is, for pharmaceutical companies, akin to a high stakes gamble where a choice should be made between trying to secure a narrow win or risking a total loss by attempting to grab a broader indication. This is particular true when there are competing products of the same class vying for FDA approvals. Could perhaps a semi-conservative approach be exploited more often, such as broadening the entry criteria, but setting more stringent primary vs. secondary endpoints? Ultimately, a failed study represents wastage of resources, and either wastage or duplication should be kept to a minimum.
  • The advent of therapy specifically targeting common oncogenic pathways give rise to the phenomenon of agnostic therapy where cancers sharing the same pathway (or biomarker) can be treated by that specific therapy, regardless of the cancer’s site of origin. Recent basket study designs allowing inclusion of all cancer types displaying a specific biomarker have proven highly successful. Not only does this led to a wider indication (and hence more sales) for the drug, but other benefits include rare cancers finally getting more approved treatments, greater economy in the number of trials required (reduced need to duplicate trials for each different cancer) and faster approvals – ultimately all this reduces duplication and enhances efficiency. Could there be greater adoption of such basket trials in the future? Presumably, even of the trial turns out negative, valuable insight to guide subsequent trials can likely be generated from subset analysis of such studies.

In the longer term, unless we achieve a cure for every cancer, advanced cancer will likely become an increasingly chronic illness. It is important to maintain quality of life and independence for as long as possible for patients on this long journey and also keeping cost of treatment affordable. This could potentially be approached from different angles:

  • Careful selection of therapy for each individual to maximize therapeutic gain and minimize exposure to ineffective therapies – this will probably entail the deployment of evermore precise predictive markers to individualize treatment. This is, rightfully, a very active area of research development, currently mainly sponsored by pharmaceutical companies as part of the development of companion diagnostic tools for the new treatment. However, it would be good to see greater participation from government or academic initiated projects from a slightly different perspective. With the increasingly widespread use of next generation sequencing, perhaps the rapidly expanding AI capabilities could be exploited in analyzing patterns of gene mutations/expressions to come up with individually tailored therapies otherwise not revealed by simple inspection.
  • Close monitoring of treatment response using ever more convenient and cost-effective means (for example new serum markers) will be important to allow more timely response to the emergence of resistance. This should again be an area where breakthroughs can make a real difference to patients.
  • In-depth studies looking into ever better scheduling of treatment would be important. At the moment, we appear content with a positive study showing effectiveness of combining 2 drugs in a standard fashion. However, it may well be worthwhile to explore other ways of combining treatments to better optimize synergy, minimize side effects (which would inevitably be greater than each individual drug) and reduce costs.
  • Recent studies have shown that certain immunologic drugs can be stopped after a fixed period even in advanced disease without detriment to effectiveness. Exploration of this type of approach should be extended to other new as well as existent therapies whenever possible in patients with advanced cancer, with the potential dual benefit of improving patient well-being as well as cost saving.
  • Finally, death is inevitable to everyone, with or without cancer. We cannot prevent ultimate death, but we can and should indeed reduce suffering. Whilst we devote our efforts to maximizing cancer cell kill, it is probably useful also to consider means of minimizing symptoms from both cancer and the treatments we give. Research into new supportive treatments should be given due attention. Just an idea: One intriguing observation is the disparity we see clinically between patients or disease types – not infrequently we see patients with similar disease loads displaying vastly different clinical course. For example, two patients with similar disease extent where one is doing quite well whilst the other is deteriorating rapidly with cachexia and debilitation – what underlies the difference in clinical course? Is it mediated by cytokines? Is it substances released by certain tumours? Surely if we can identify and ‘target’, then we can potentially intervene to bring about clinical benefit.

Despite huge steps and impressive breakthroughs over the past decade, there is still much that remains to be discovered in cancer. Coordinated effort is necessary to achieve the best outcome whereby industry, frontline physicians, governments and academic institutions should work closely together to face this common enemy, and in this long drawn-out war, sustainability is probably as important as effectiveness.




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