Successes in biotechnology, like in most branches of science, have been built upon the shoulders of major failures. In a new book, Good Genes Gone Bad, biotechnologist Dr Narendra Chirmule studies the histories of several major drugs and treatment protocols from across the world and finds that there are recurring patterns in the way they came to be: most commonly, the final, life-saving drugs and vaccines and medical technologies developed after particularly galling failures.
These stories include the treatment of the genetic clotting disorder haemophilia, the development of the rotavirus vaccine, preventing HIV infection, activation of the immune system to treat cancer, gene therapy for treatment of diseases caused by gene-defects/mutations, cell therapy for the treatment of leukaemias, and finally the development of the first biologic drug for treating breast cancer by Indian biotech company Biocon, where Dr Chirmule, PhD, used to head R&D before founding SymphonyTech Biologics, a company focused on the statistical, technical and quality aspects in drug development.
In an interview with Lounge, Dr Chirmule talks about finding the patterns of success and failure – and how they correlate.
What motivated you to write this book?
My experiences in drug development in the various places I worked in during the course of my career took me through several failures. Colossal failures. In all cases, these failures were followed by phenomenal successes. Indeed, were it not for the failures, the paths to success that followed would have been hazy, long-winding and tiresome. To appreciate success, it is important to chronicle and recognize the contribution of the things that went wrong.
The process of drug development needs a seismic change. The COVID-19 pandemic has highlighted the possibity of developing safe and effective drugs and vaccines in unprecedent timelines. The data from the lessons learned from these processes need to be collected, analysed, and applied to all drug development in the pharmaceutical and biotechnology industries. Hence this book.
You have divided this book into seven different narratives of diseases/ drug therapies used to counter them. What was the reason for choosing this narrative structure for this book?
The narration of this book follows a pattern. I love the number seven. It is my date of birth in January; my first day of college was on 7-7-77; there are seven days in a week; there is a seven-beat rhythm (taal) in tabla (rupak); there are seven continents, seven seas and seven colours of the rainbow. The lists I make in the book have seven points. There are seven stories I have chosen to tell. But why seven?
Why not, I say? Making a list of seven requires effort. It is very easy to make a list of three things. Try making a list of seven for everything; you have to think hard and deep.
You seem to have found a distinctive pattern that interweaves the stories of how several of these therapies were developed. How did you see this pattern and what made you think these patterns had narrative power?
I love finding patterns in everything. Its part of being observant, and curious. I am constantly looking for interesting patterns for ideas of what to paint, how to teach (since I teach a lot), and pattern-recognition is an integral part of scientific research. Hence, when I observed, and researched drugs that failed, it was obvious that “what goes down must come up”. It is possible that is the process that I imagined for the stories in the book.
Why is it so difficult to develop new treatment protocols?
The low-hanging fruits in drug development have been plucked. Treatments of many diseases have been developed, from clean drinking water, penicillin to paracetamol. The human body is extremely complex. The processes and mechanism of disease pathogenesis is multi-factorial. Hence finding drugs that can “cure” diseases requires a deep understanding of disease biology. With the advent and power of computational and engineering technologies, the ability to interrogate the biological systems has increased exponentially. It was (and continues to be) difficult due to the multi-factorial nature of interactions in disease pathogenesis. The combination of biological and mathematical science can transform drug development
What are some of the conclusions we can draw from the way covid-19 vaccines were developed in terms of speed and efficacy? And does this effectively act as a critique of the way the scientific community may sometimes slow their own progress in an abundance of caution?
The seven learnings that I can list are:
I am sure there will be many more lessons when we ask more people to comment.
The scientific community has done an outstanding task of developing drugs and vaccines. The public at large has for-the-most-part also contributed positively. The overall knowledge and the pace of sharing it has been extra-ordinary (compared to the 1918 pandemic).
6. What long-lasting effects will this have on the scientific community and on drug development on the whole?
The learning from COVID-19 will surely have a long lasting effect on drug development. All the points above will need to be continued. The high level of collaboration, funding, regulatory involvement, community participation and mentoring has the potential to transform drug development. There is a lot to do. Many diseases to be treated. Cures. The book is one small step in enhancing the knowledge base of drug development for both the scientific community and public-at large.