Two years into the COVID-19 pandemic and we are still unsure of when it will end. However, what we are certain of is that it has changed the way we live. With industry definitions altered and business boundaries redrawn, we are looking at a whole new construct for the life sciences sector. One that hinges on the holistic health and wellness of one and all and includes all facets of quality of life.
The world’s expectations of technology have grown multifold in recent years. We have ubiquitous and connected devices that capture a range of health and wellness parameters. Customers—individual consumers and healthcare professionals (HCPs)—are increasingly expecting hyper-personalized wellness and care. What does that mean for the life sciences industry and how can it adapt to the customers’ changing demands?
Future trends in life sciences
Here are some trends that are transforming the core areas of life sciences industry such as customer experience, research and development, manufacturing, and supply chain:
Customer experience: Life sciences companies are focusing on reducing the patient burden and the treatment threshold with the help of advanced technology. By bringing a seamless integration right from the clinical bench to the point of care (POC), and providing care at home, companies intend to improve the patient experience, in areas like therapeutic compliance and efficacy through home-based monitoring and administration of drugs at POC. This data helps with insights that will enable positive interventions in the quality of life of patients.
Drug discovery: Bringing a new drug to the market is a lot faster now – no longer does it take 10 to 15 years. By and large, we are witnessing three important tracks of research in biopharma:
- Meeting unmet medical needs in domains such as allosteric drug discovery, multi-specific drugs, and protein families, for example, kinases and G-protein coupled receptors (GPCRs) for immunology and oncology
- Personalized therapy, which requires translation of drug from bench to clinic through artificial intelligence (AI) by leveraging data effectively.
- Quantitative sciences, where model-based drug discovery is leveraging AI and machine learning (ML) extensively to create an end-to-end data-driven modeling pipeline. For instance, the pipeline created by the Accelerating Therapeutics for Opportunities in Medicine (ATOM) consortium has many global pharma and medical device companies as well as academic institutions as its members.
Devices and diagnostics: Organizations are moving away from the word ‘patient’ by attempting to detect the disease even before the symptoms arise. Care and diagnostics are moving closer to the customer. Pharma companies are focused on improving therapeutic efficacy by collaborating with medical device companies and constantly innovating for a targeted drug delivery system. All the diagnostic companies today are focusing on self-diagnostics to detect diseases and syndromes well in time. Another example is the rising digital adoption in the field of surgery. Robot-assisted surgery and minimally invasive surgery are improving the quality of life with better implants.
Manufacturing and supply chain: We believe the future of manufacturing is Neural Manufacturing™—where supply chains are adaptive, resilient, and scalable, and manufacturing processes are modular and highly customizable.
Ecosystems comprising manufacturers, pharma companies, suppliers, and logistics service and public health providers are gaining prominence. A recent example of ecosystem play has been the COVID-19 vaccine management that boasts of several innovations such as cold supply chains, and dry ice innovations.
Enabling personalized medicine in life sciences: A new realm of possibility
The pace of innovation in life sciences is certainly going to accelerate. We will see a wider evaluation and adoption of IoT, RFID, 5G, quantum computing, digital twins, blockchain, AI, ML, cloud, among many other technologies. Most importantly, data, AI, and ML will play a pivotal role in personalizing medicine and driving commercial success, while a consortium approach will be important to share data for research. There will be more focus to go from probabilistic to deterministic decision-making to improve efficiency of AI systems.
We will also see the emergence of the micro supply chain soon. Drone-based medicine delivery also shows great promise. These are finite, decentralized, agile ‘mini-operating models’, with flexible supplier contracts and relationships with manufacturing closer to the point of purchase.
The future indeed looks exciting where the consumer demands personalization. This provides ample scope for reimagining the life sciences value chain, and cross-industry collaboration.