Neil Thomas, partner and head of health care and life sciences for EMEA at Infosys Consulting, discusses the three tech-enabled R&D opportunities to drive cost-effective transformation that are still missing in the life sciences industry.
Key insights:
- There are several opportunities to drive efficiencies within innovation in the pharma and life sciences industry that have not yet been recognised or addressed.
- Blockchain technology can address some of the data challenges associated with managing vast sets of clinical trial data, by ensuring that patient data is protected and anonymised whilst providing greater transparency.
- Combining big data and AI with clinical trials and personalised medicine would reduce cost of drug development and time required to bring a drug to market.
- 3D printing technology can support the development of small-batch medication, allowing for the fast development of prototypes and custom medications for individual patient.
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The pharmaceutical manufacturing and life sciences industry is in a state of significant disruption, and subsequent transformation. The fallout from Covid, combined with supply chain and global geopolitical challenges, plus the reality of climate change, has caused higher costs, difficult operating conditions, and market flux for the entire industry. However, these threats also run alongside an explosion of technological advancement.
The pharma industry is in a position to realise radical transformation by building on today’s budding technologies – particularly in terms of research and development (R&D), which is often the most challenging area for life sciences companies. While considerable breakthroughs have been achieved through digitalisation, opportunities to drive efficiencies within innovation are being missed.
Driving efficiencies with blockchain
As with all sectors, data is the true lifeblood of life sciences, but despite leaps in its use in R&D, there is still a lack of effective strategies that ensure the safe and effective use of big data to drive cost-effective innovation. Consider blockchain, a technology already used to significant effect in the financial services sector, similar in its high security and data regulation levels.
Clinical trial data is an essential component of drug development, and the integrity and security of this data are critical to ensuring patient safety and bringing new drugs to market. However, to realise the power of data within R&D, companies must be able to securely access and analyse sensitive data at scale.
As recent research published in the International Journal of Molecular Sciences highlights, “one of the major problems in the use of big data in medicine is that medical data has been collected across different states, hospitals, and administrative departments using different protocols.
Therefore, new infrastructure resources are required to better cross-examine the medical data through proper collaboration between different data providers.”
Blockchain distributed ledger technology can help to address some of the challenges associated with managing vast sets of clinical trial data, including data privacy, security, and transparency - especially when considering the collaborative nature of today’s R&D. By storing clinical trial data on a blockchain, pharmaceutical companies can ensure that patient data is protected and anonymised while providing greater transparency and accountability to the numerous stakeholders involved in the process.
Furthermore, blockchain technology can help streamline data management. Automating processes such as data verification and validation reduces the time and cost of managing clinical trial data, freeing up resources to focus on other aspects of drug development. Trust, transparency, and immutability - the three fundamentals of blockchain - align perfectly with the requirements of the pharma industry. By improving data security, transparency, privacy, and efficiency, blockchain can help to improve patient safety, increase trust in the drug development process, and accelerate the pace of innovation in the industry.
Making personalised precision medicine possible
One of the pervasive issues in the industry is the escalating costs of R&D. Not only that but patients and governments increasingly want more for less, especially in this new era of personalisation. As Elias A. Zerhouni, MD, former director of America’s National Health Institutes and Centres, accurately predicted, we are now in the era of P4 medicine – predictive, personalised, pre-emptive, and participatory. Now individuals expect services to be tailor-made and targeted to their specific needs.
Personalised precision medicine aims to provide individualised treatments based on a patient's genetic makeup, lifestyle, and other factors and relies heavily on the effective use of big data and AI. This is where blockchain technology could come into its own, enabling big data and AI to come together to develop hyper-personalised medicine at scale.
While personalisation is often associated with higher costs, AI can reduce the cost of drug development for hyper-personalised medicine by enabling researchers to predict drug efficacy and safety more accurately. By analysing vast amounts of data, including genetic data, medical histories, and drug response data, AI can identify biomarkers and other indicators that can predict how an individual patient will respond to a given drug. This can reduce the need for expensive clinical trials and help researchers identify promising drug candidates more quickly. AI-enabled hyper-personalisation approaches can also help researchers design clinical trials that are more targeted and efficient, reducing the cost and time required to bring a drug to market.
As the above research summarises:
Advanced machine learning approaches such as artificial intelligence and deep learning represent the future toolbox for the data-driven analytics of genomic big data. The emerging progress in these areas will be indispensable for future innovation in health care and personalised medicine.”
Putting 3D printing into practice
Developing personalised medicine through AI opens many doors, but production is another challenge. This is where 3D printing technology can support the development of small-batch medication, whether for prototyping or personalisation. For example, 3D printing can allow pharmaceutical companies to easily adjust the production process to accommodate small batch sizes, allowing the fast development of prototypes and custom medications for individual patients, supporting the aim of ‘batch of one’, through personalised precision medicine.
By enabling more targeted drug development, more efficient clinical trial design, and more accurate prediction of drug efficacy and safety, AI is critical to R&D and will be fundamental to the realisation of personalised medicine. Add to this the secure foundation of blockchain and the potential of 3D printing to support effective production, and the roadmap for future medicine is paved with today’s most innovative technologies. Through focused digitalisation within R&D, the industry can realise innovative channels for growth that could redefine life sciences for the better of all.