The global pandemic has forced the life sciences industry to innovate rapidly. While there is excitement about new tidings, there is also anxiety about the unknown future. The paradigm shift has brought together scientists, regulators, and commercial business teams on a common platform to solve everyday problems. Emphasis has been given to a data-centric approach, implemented through deploying new tools based on Artificial Intelligence (AI), Machine Learning, and cloud computing in all stages of work, from early R&D to post-market monitoring. Moreover, these new challenges have also triggered increased investments in R&D in the bid to be self-reliant and reduce risks due to global geopolitical issues.
An essential aspect of responding to the pandemic is increased collaboration between academia and the life science industry. This facilitates sharing of resources and knowledge in joint fields of interest. Whereas academic institutes can validate research queries, the corporate sector can help de-risk investment in core research and expand capabilities. Collaboration is crucial for driving scientific innovation and discovery, particularly with the involvement of young, aspiring scientists in the industry. Life science industries are keen to foster talents by giving first-hand experience with the state of art tools and techniques by setting up specialised hands-on training programmes coherent with the academic syllabus. One programme that can be leveraged in this direction is the Merck High Skill development initiative, an initiative in collaboration with CSIR-IMTech in which we have worked towards scientific skill development.
Biotechnology and health care are crucial components of the life sciences sector, and both have seen significant growth in recent years. For India, in particular, the success of the country’s vaccine manufacturing capabilities during the Covid-19 pandemic has demonstrated the value of its entrepreneurial, innovative, and domestic talent-driven approach. The global market has also been positively impacted by the rise in opportunities and advancements in drug development and vaccine manufacturing. Furthermore, the success of mRNA vaccines and accelerated approval processes have led to a surge in vaccine-related revenues.
In addition to the growth in the vaccine market, both the consumption and exports of diagnostic and medical devices are expected to increase significantly in India. The expansion of biotech incubators and start-ups will also play a key role in driving the success of the Indian biotechnology industry. Similarly, the global biotechnology market is supported by vital government initiatives to modernise regulatory frameworks, improve approval processes and reimbursement policies, and standardise clinical studies. These efforts are helping to promote the biotechnology industry’s growth and improve people’s lives worldwide.
The approach of India’s life science community towards self-reliance is two-fold: one, the indigenous development of technology, and two, the indigenisation of technology in alignment with national priorities. Although India is a crucial supplier of medicines and vaccines, India needs to be self-reliant on certain raw materials and research reagents to ensure steady output and revenue.
Manufacturing costs across industries have increased significantly while productivity continues to decline. To address this concern, notable transformations such as organisational restructuring and operational overhauls are being made. Adapting the process improvement, like digitising the inventory process, can help in obtaining real-time updates about stock levels and location, planning experiments, and improving the efficiency of lab operations. Such breakthrough solutions would also help data traceability, regulatory compliance, and audit readiness. One can expect more companies to adopt this approach in the coming years as they seek to implement innovative and cross-functional transformations to achieve sustainable productivity improvements.
Adaptation of new technology is a significant factor in tackling future challenges. Artificial Intelligence (AI), aided by machine learning (ML) techniques such as Natural Language Processing (NLP), promises to enhance the capabilities of the life science industry manifold by extracting insights hidden in data rapidly and effectively. Big tech companies like Meta (the parent company of Facebook) and DeepMind (a subsidiary of Alphabet, the parent company of Google) can now solve millions of protein structures through AI quickly. This can help scientists better understand the functions of proteins, aiding in developing new drugs. Combined with a suite of computer-aided drug design (CADD), AI and ML will expedite lead identification in drug discovery projects. It will be a one-stop shop bringing together a bevy of tools for modelling the protein, docking the lead candidates, and scoring the molecules based on binding efficiency.
Genomics, 3-D bio-printing & disease modelling, robotics, and advanced communication solutions also have the potential to help clinicians rise to the challenges of 21st-century health care. Implementing Big Data in Life Sciences can look like next-generation sequencing (NGS), where vast amounts of data are produced quickly, and introducing technology evaluates this data.
The emerging technologies also bring chemists and computer scientists together – aiding medicinal chemists to identify the synthesis route. With the available resources and requirements, scientists quickly go from imagining what is possible to test what is probable. While low-code platforms, which require little to no coding experience, are indeed gaining popularity, Life Sciences will continue to be on the lookout for digital experts as reliance on technology continues to increase.
Technology can transform life sciences- but only if we develop and nurture links between medicine, technology, and business. As the life sciences and technology sectors continue to converge, greater cross-sector collaboration is the key to realising the potential of the life science revolution. Convergence in action like drug development and screening utilising knowledge of life sciences and the power of AI and ML, Genome mapping and utilisation of Big Data to predict the responsiveness of certain tumours to chemotherapy and personalised medicine are revolutionary examples driving the trust in collaboration and convergence across sectors.
Given the visible positive impact of convergence in life sciences, re-imaging the architecture of the life science sector in which industry convergence is a focus is what we need to advance the standard of research and patient care in these changing times.
The future of the Life Sciences industry will be more digital and data-driven. As organisations and individuals contribute more resources to enable a higher level of personalisation and automation in manufacturing, the trust of patients and consumers in new technologies and treatment methods will increase. By fostering more collaboration and partnerships between government, industry, and academia and focusing on industry convergence, we can unleash the full potential of the life sciences. From operational restructuring to increased deployment of digital solutions in diagnosing and treating diseases, we can pave the way for revolutionary advancements in human health and make a lasting impact on humanity, where success will not be measured by profits alone.
The article has been authored by Dhananjay Singh, head of science and lab solutions, India, at Merck Life Science.