Personalized Medicine – Myth or Reality?


By Sreesha Srinivasa, PhD

Associate Vice President, Research and Development, Biocon Research Limited.

Personalized medicine is a buzz word these days in pharma/biotech industry, academic medical centres and Healthcare sector. What exactly is “personalized medicine? Is it already here, is coming soon or just a mirage?

In my personal opinion, personalized medicine word is heavily misused and it is unlikely that we will achieve truly personalized medicine at least in our life time.

aIn simple terms, personalized medicine can be defined as “individualized matching of therapies and regimens to a person’s disease condition” as depicted in the graphic. For eg. a cancer patient with A+B+C mutations is matched with a cocktail of 1+2+3 drugs vs. another patient with A+B+D mutations is matched with a cocktail of 1+2+4 drugs. With the help of genomic tools, the scientific community has made tremendous progress in mapping out the underlying cause of diseases in individual patients be it repertoire of mutations, aberrant expression, epigenetic changes etc. It’s well established that there are hundreds of driver mutations in tumors of each cancer patient of a specific tumor type with only a small subset being common among them.

Similarly the set of aberrant molecules such as cytokines, chemokines, receptors, immune cell markers could be different in each patient with an auto-immune disease such as Psoriasis, Rheumatoid Arthritis etc. Unfortunately, developing drugs to many of these aberrantly regulated targets and pathways has been scientifically and technically challenging. Thus, we don’t have choices of approved drugs to pair with most of the dysfunctions in individual patients. Hence, at this time the best we can hope for is more of a “precision medicine” rather than a “personalized medicine”. Biomedical community is striving towards precision medicine in many important disease areas.

One disease where I believe we certainly are in the realm of precision medicine is Oncology. You may ask what this “precision medicine” is. Unlike the medical practice of the past where everyone with a particular disease received one size fits all therapy, we have been able to define diseases a little more precisely based on molecular characteristics and match subsets of patients with targeted therapies.

One of the early examples is the molecular sub-classification of breast cancer into hormone positive, Her2+ and triple negative. Hormone positive breast cancer patients are treated with anti-estrogens and Her2+ breast cancer is treated with Herceptin with remarkable improvement in long term survival. More recently, a further refinement in classification of breast cancer based on gene expression profiles with distinct prognosis and recommended treatment regimens has shown further promise.

bAnother disease that has seen rapid progress in molecular sub-classification and therapeutic development is Non Small Cell Lung Cancer (NSCLC). Currently NSCLC is diagnosed and classified both histologically and molecularly based on mutations in specific oncogenes.

A patient with EGFR mutation is treated with an EGFR tyrosine kinase inhibitor such as Tarceva or Iressa and a patient with an ALK+ tumor is treated with an ALK tyrosine kinase inhibitor. Drugs that target other oncogenes are in clinical development and have shown early promise.

It’s worth mentioning that not all patients that are positive for the markers mentioned in the examples above respond to the respective drugs but the response rate is significantly higher than in the general unselected patient population. Most of the marker negative patients don’t achieve any benefit. Hence, the precision with which we can identify the relevant population is not perfect but better than what we could do in the past.

You may ask, how one goes about developing “precision medicine? There is no secret recipe, set process or road map. It’s a highly iterative process from “bedside to bench to bedside”. You can start with precisely defining a subset of patients based on molecular analysis of biological samples. Her2+ patients were identified first as a subset of breast cancer patients with poor prognosis. Her2 receptor then became a drug target. On the contrary, EGFR mutant patients were identified as a subset of Non Small Cell Lung Cancer (NSCLC) patients that showed remarkably superior benefit to Tarceva & Iressa, EGFR tyrosine kinase inhibitors. In this case precision medicine was achieved by careful observation and analysis of samples from clinical trials of the drug. In another example, responder patient population was identified during the discovery phase of the drug. ER+ luminal A subtype of breast cancer was identified as a potential sensitive patient population to a CDK4/6 inhibitor through a large scale cell line screening. This indeed proved to be the case in the clinic as evidenced by the approval of Palbociclib for this patient population.

Any novel drug discovery program needs to keep asking “how do we translate the discovery into clinical success” at every step. It could start with the question “how relevant is the target to the disease process in patients, not just in cell lines and animal models”. Then come the questions:

  1. Is the drug modulating the target at physiologically relevant concentrations?
  2. Is there a correlation between the target modulation and efficacy?
  3. What is the mechanism of action of the drug?
  4. Do we have biomarkers and assays developed and validated to test the effects of the drug in early clinical trials?
  5. Do we have a hypothesis for responder/non-responder population?
  6. If not, do we have a strategy for investigating this question in early clinical trials?

More the number of questions we have clear answers to, better is our chance of clinical translation. However, these are not easy questions to answer. We have to have deep domain knowledge and commitment to detailed scientific investigation of the drug in discovery and clinical development rather than checking all the boxes. I believe that aspects of precision medicine will reduce the cost of drug development by reducing attrition in late clinical phases and by having smaller clinical trials due to the larger effect size expected. The impact of precision medicine on the patients and the society at large will be much more than incremental which is the norm for most of the newly approved drugs.

2 Comments Add yours

  1. amberrose93 says:

    It’s definitely reality, just look at how people with different cancers react to various drug combinations


  2. GJ says:

    I agree with precised medicine to personalised medicine in future. We should foresee the drug in discovery as a clinical candidate and mould are experiments in that direction as ultimately we have to take it to patients. they may have entirely different pharmacodynamics when compared to animals in models. as we all know clinical studies are very expensive so is there any possibility to have a genomic database in future? yes we might have some preliminary kind which tells us about genomic sequence etc. but can we have such extended database which has so called Big Data of correlation of biomarkers and their levels with population types. how they vary with age gender diseases situation. and more on that how to use that data for simulating in pre-clinical studies. can we have database which let us simulate that real time data with existing genomic types in our database and predict so called personalised medicine rather than precised medicine? well the blog is really very good but can we really have personalised medicine in future? so that we can develop that in drug discovery rather than testing population and evolving with one; which takes time and delays. 👍


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