Life Sciences Pulse

Embracing an Analytics-led Approach to Drug Development for Infectious Disease

March 28, 2018

Let’s face it: India is a subtropical country struggling with poverty and with a still developing infrastructure. While much of the West’s population may be struggling with cancer and heart disease, the subcontinent’s climate and low level of hygiene has turned our country into a hotbed for infectious diseases. Approximately 17.9% of deaths between the ages of 25 and 69 years are attributed to afflictions such as malaria, tuberculosis, and diarrhoea. Needless to say, the infectious disease burden is endemic to developing economies like ours and low income countries (LICs) across the world.

Many of the existing drugs available in the market fail to effectively target disease-causing pathogens and mitigate associated symptoms, with every subsequent dose helping the bug develop tolerance. This problem is not just limited to antibiotics and the likes. Once alcohol-based hand sanitizers became a mainstay for fighting the simple staph infection-causing bacteria Staphylococcus aureus, the pathogen itself altered its genetic makeup to transform into a deadly drug resistant superbug.

This is why pharmacological R&D needs to focus on discovering new drug molecules capable of targeting and modulating the desired pathways in the pathogen. Doing so, however, will require extensive understanding of drug action mechanism. Since many of the currently available drugs fail to act on the pathogen as intended, there is a need to identify new drug targets – which are typically proteins playing a crucial role in signaling, metabolism or gene regulation in the pathogen. Pathogens, because of their ability to evolve, are known to change their genetic constitution. It is therefore equally necessary to understand how this genetic variability could affect the mechanism of pathogenesis and the development of resistance towards drugs.

Unlocking the DNA of Diseases

A single gene or protein does not work in isolation during an infection. Rather, there is an entire network of intermolecular interactions – both in the pathogen and the host cells – at work. Systems biology can be used to computationally model such multidimensional networks for providing new insights into disease mechanisms, identifying alternative drug targets, and predicting drug action mechanisms. Such a systems-level infection model can be further enriched with information on strain- and patient-specific variations, metabolic pathways, and protein-protein interactions, to name just a few.

The business case is strong for investing in this technology. The identification of novel drug targets opens up avenues for drug discovery. It can not only accelerate pharma R&D programs but also enable them to test the drug in silico during the early stages of development before moving into riskier, more expensive experimental trials. This is, once again, something that computational models excel at supporting. Infection models can simulate drug action modes for discovering possible undesired pathways modulated by a drug – helping companies ensure that new products don’t cause undesired side effects.

Investing in the Future of Medicine

Finding the means to control or, better still, eradicate infectious diseases is inevitably a matter of concern for India, and the country must lead the way in making efforts to do so. With a large pool of skilled manpower to drive research and innovation, India should be able to make satisfactory progress in this field. The need to encourage data-driven research on infectious diseases has been recognised by funding bodies from the government as well as the industry. The Tata Trusts is investing USD 70 million (INR 458 crores) in setting up the Tata Institute of Genetics and Society in Bengaluru, India – aimed at completely eradicating malaria and other mosquito-borne diseases in the country. More recently, the Indian Health Fund (established by the same Tata Trusts)announced it would invest in research for improving prevention, diagnosis, and treatment of tuberculosis and malaria. The approach adopted would be multidisciplinary, making extensive use of data science and other technologies.

The Infosys Foundation has also announced a grant of INR 50,000,000 to fund the Centre for Infectious Disease Research at the Indian Institute of Science in Bengaluru (IISc) for supporting research on a broader spectrum of infectious diseases.

Systems-level modelling of infectious diseases and drug actions can take us further into the era where digital technologies will increasingly be used to provide better solutions in healthcare. If you wish to find out more about how systems-level modelling can help us fight infectious disease, please do leave a comment.

Siladitya Padhi is a scientist working with the Life Sciences unit of TCS Innovation Labs, Hyderabad since March 2017. Through his research, he aims to find novel solutions for treating diseases by employing structure-based and systems-based computational biology methods. He has a PhD from IIIT Hyderabad.