The Indian pharma sector needs more actionable and optimised drug development and delivery models driven by data and new-age technology to provide greater value and enhance outcomes By Lakshmipriya Nair
As the pressure to reduce costs and demonstrate greater value intensifies, it is becoming increasingly evident that India Pharma Inc can continue on a growth path only by improving its R&D efficiency. And, a radical reconstruction of its existing drug development ecosystem has emerged as one of the most urgent steps in this direction. So, how is the industry tackling the aspects that complicate and impede drug development? The answer is clear. By harnessing new digital technologies such as automation, AI and IoT to disrupt clinical research and jumpstart the transformation of the drug development lifecycle, from discovery to clinical proof of concept (PoC).
Dawn of a tech renaissance…..
As the industry grapples with falling levels of productivity, drying R&D pipeline, increasing trial complexities and greater regulatory scrutiny, both domestic players and MNCs in this sector are increasingly banking on technology to streamline the pharma value chain by gaining higher economic value for newer treatments, augmenting drug approval rates, enhancing efficiencies and lowering the associated costs of drug development.
Dr Ajay Kumar Handa, President, Research & Development, Cadila Pharmaceuticals explains, “With the increase in the regulations in the pharma market and the evolution of the pharma market, drug development and drug discovery has evolved as well. Therefore, automation and digitisation are an integrated part of our processes. For e.g. use of technologies like artificial intelligence and machine learning to accelerate pharma R&D.”
So, let’s examine the major transformations being ushered by these technologies. Enabling real-world evidence: The role of data analytics in steering greater efficiency and transparency in drug development cannot be overstated. As Swetabh Pathak, Co-founder and CEO of Elucidata, a data analytics company informs, “Advancement in technology has shifted the focus in drug discovery from data generation to data analysis. With biological data being produced at an unprecedented rate today, pharma companies require faster data analytics to gather relevant insights in time.”
Thankfully, as a result of progressive data management technology, analysing vast amounts of complex data has become much easier and at a pace more rapid than ever before. For instance, with the help of technology, R&D stakeholders of pharma can evaluate how a drug or class of drugs perform in actual medical settings and work in collaboration with academia to identify new medical treatments for unmet medical needs through drug discovery. Real-world data also enables target based drug discovery and development procedures.
Dr Handa cites an example to explain, “Target-based drug design with the use of high throughput screening (HTS) methods like QSAR along with modern research disciplines such as genomics, proteomics, and metabolomics, help improve the quality of drug discovery process.”
Thus, it is now possible for pharma companies to leverage real-world evidence from sources such as wearable devices, mobile apps, claims data or electronic medical records (EMR) for significant actionable insights to facilitate more medical breakthroughs and acquire competitive strengths.
Reducing costs: The sphere of drug development is extremely competitive and capital-intensive. As Pirthi Pal Singh, a formulation development expert apprises, “The traditional drug discovery approach can take upto 10 to 15 years and about $2.5 billion investment to bring a molecule from conceptual stage to market.” Studies also reveal that the costs of developing a new drug doubles every nine years. But, with mounting pressure to make drugs affordable, the need to bring down the cost of drug development has become very urgent.
The pharma industry has realised that the solution to this dilemma lies in effectively harnessing technological advancements to bring down the associated costs of drug discovery and development. In fact, a FICCI-KPMG paper on artificial intelligence and advanced analytics in pharma reveals that AI in drug dosage error reduction alone can save $16 billion by 2026, worldwide. A Morgan Stanley Research Bluepaper, “Digitizing Drug Development: How Much Can It Save?” highlights that with effective deployment of IT, “companies could realise more than 20 per cent in potential annual research and development savings by 2030. That translates to an average savings of $330 million per approved drug.”
Enhancing efficiencies: Technologies of automation have a huge potential to and radically fast-track compound screening and other aspects of R&D, alongwith boosting efficiencies. They can also provide significant benefits in terms of overall quality and compliance. As Arno Tellmann, Head of Global Drug Development India for Novartis emphasises, “Utilising the latest emerging technologies helps us capture better data – making us smarter and more efficient in the ways we approach drug discovery and development.”
John Fowler, Chief Operating Officer, Piramal Pharma Solutions also elaborates on this point and says, “Digital technology is being used today to enhance predictability of in-vivo behaviour of drug molecules, to ensure quality at each stage during product development using QbD principles, etc. This is critical in enhancing long term R&D productivity.”
Elaborating with an example from his own organisation, he informs, “We, at Piramal Solutions, have developed an indigenous software for QbD that enables a standardised and scientific approach, thus accelerating the overall process of product development. We also use automated in-process tools that increase productivity and enhance predictability for commercial scale during lab development itself by providing early information on physical behaviour of the formulation. Thus, the solution focuses on providing the best combination of speed, costs and uncompromising quality.”
Thus, investments in the right technologies can help shorten cycle times by speeding the delivery of information and insight and expedite the path to progress for pharma companies.
Ensuring quality and compliance: The entire drug development process is getting rapidly modernised with the help of transformative technologies such as IoT and AI. As the FICCI-KPMG report on AI and data analytics in pharma highlights, “Increasingly AI and data analytics in pharma industry is transforming processes from the initial R&D level to the after-consumption stage.”
Lending more clarity to this point, Fowler enlightens that enabling technologies are being applied (by pharma companies) right at an early stage of evaluation of new chemical entities (NCEs) to enhance drug solubility, to modulate PK, to enhance efficacy of the drug, etc. “Automation and digitisation help effectively deliver on quality. Using real time process analytical tools (blend uniformity, in-process estimation of particle size) and estimation of drug release while testing the exploratory development samples of formulation help us continuously prevent deviations and optimise delivery,” expounds Dr Handa.
Singh also apprises that self-learning AI platforms like Artificial Neural Network (ANN) and Design of Experiment (DoE) help in understanding inter-parameter interactions and further support composition and process optimisation. He also informs that these platforms, “help in developing a multivariate correlation to obtain a quality drug product, based on understanding of cause-effect relationship between formulation ingredients/process parameters and quality target product profile. Thus, it is evident that these technologies, if applied at each step of the value chain, can augment the overall quality and compliance of pharma products, as well as optimise and accelerate the bench-to-bedside process of crucial medicines.
Driving more value: A report by Deloitte Insights titled, ‘Digital R&D: Transforming the future of clinical development’, posits that “digital technologies can help companies develop a better value proposition by operationalising the drivers of patient value and achieving significant advances in study methods that traditional approaches cannot deliver.”
For instance, the report highlights that the use of cognitive technologies – especially advanced analytical capabilities such as machine learning provides “insights that may suggest potential new indications, a different safety profile or response to treatment in certain patient subgroups, or predictions around the likelihood of compounds to succeed in trials.”
Tellmann affirms this point of view and states, “Digital technologies and data science have incredible potential to unlock the next chapter of medical innovation. Integrating digital into the way we work has enormous benefit for Novartis by improving the way we work with data – one of the most valuable assets we have as a company.”
He further informs, “Applied to the drug development process, we are leveraging digital tools to transform how we develop medicines, and the efficiency with which we do so. We are systematically improving all elements of clinical development by using Machine Learning to conduct predictive analyses on our operational data resources to facilitate data-driven decision-making in current and future trials.”
Piramal Pharma Solutions has also invested in these technologies to enrich their offerings to the pharma sector. Fowler updates, “In October last year, Piramal Pharma Solutions also launched their ‘Xcelerate Integrated Solutions’ platform to address the increasing demand from pharma firms for preferred collaboration with organisations that can provide world-class solutions across the entire drug-cycle. The platform sets the foundation through which customers can accelerate their programmes from clinical through approval and launch.”
In fact, even the regulators have taken note of the huge potential that these new age technologies offer to reforming the pharma sector. For instance, the FDA has allowed the usage of wearable technology for patient reporting as part of clinical trial design. The pharma sector in India too has been experimenting with digital technologies to varying degrees to integrate them into routine drug discovery and development operations for delivering value to all its stakeholders.
Upcoming trends in drug development and delivery
- Oral delivery of vaccines and peptides
- Developing Insulin which is suitable for oral dosage form
- Use of technologies like 3D-Printing to bring down costs
- Nanoparticulate drug delivery systems and Chronotherapeutic drug delivery systems
- Continuous manufacturing – Increased quality, process throughput, and yields
- Digital pills
- Serialization (A comprehensive system to track and trace the passage of prescription drugs through the entire supply chain reduces counterfeiting)
- Dose re-conciliation in multiple dose delivery system
- Robotic analytical testing procedure to estimate the in-vitro drug release which will provide results with high accuracy and consistent speed
Source: Dr Ajay Kumar Handa, President, Research & Development, Cadila Pharmaceuticals
….but true transformation is a tall task However, undergoing a true digital transformation, as the Deloitte report rightly describes it, is a “complex, resource-intensive, and lengthy undertaking.” It points out that pharma companies and CROs will “need to overcome several challenges to realise the potential of digital in clinical development: immature data infrastructure and analytics, regulatory considerations, and internal organisational and cultural barriers.”
The report also recommends that the life sciences sector should “consider building updated data infrastructure and governance, engaging early with regulators to discuss new technologies, and developing a measured approach to evaluating and implementing technologies within their organisations. CROs can enable this change by advancing interoperable digital platforms and vetting promising technology applications.”
Thus, despite digitalisation and automation being the answer to tackle complexities and challenges in the drug development, the pharma industry has been actually unable to unlock their true potential to improve innovation, productivity and profitabilty in this arena. Even though pharma majors have formed innovation groups and invested in some pilot initiatives to leverage new-age technology, the outcomes have been in terms of incremental innovation and more often than not, have been unable to achieve scale. So, is there a cure to this conundrum?
Open science and collaborations
Experts believe that the solution could lie in moving towards a new open science ecosystem. In fact, many opine that it should be the default approach across the research enterprise. The Deloitte Insights report also suggests, “Cross-industry consortia could help advance the industry as a whole by offering a forum to share early successes and supporting the development of standards.”
Interestingly, Open Source Drug Discovery, a Council of Scientific and Industrial Research, India (CSIR)-led Team India Consortium has been offering a collaborative drug discovery platform. Its vision is “to provide affordable healthcare to the developing world by providing a global platform where the best minds can collaborate and collectively endeavour to solve the complex problems associated with discovering novel therapies for neglected tropical diseases like TB, malaria, leishmaniasis, etc.” Its Wikipedia page informs that “this programme has a global community with over 7500 participants from 130 countries comprising researchers, academia, students, industries, educational institutions and so on.”
Multiple digital tools used in day-to-day pharma processes
- Project management software /tools helps tracking the development programme.
- Inventory controls (RM/PM and other miscellaneous).
- Data integrity – online data recording /mapping of process parameters, e-lab book.
- Paperless documentation: Online entry of Test Analytical test request and Report, E-lab note book, e- protocols/check list in various stages of development.
- Electronic document management system (LIMS).
- Quality by design in estimating the end point in granulation, ejection force.
- Accuracy in results through validated excel sheets.
- Documentation storage and archival (PDF conversion of other formats).
- Management and tracking of Subjects in clinical studies.
- Digital print outs which ensures the Data integrity and data compliance.
Source: Dr Ajay Kumar Handa, President, Research & Development, Cadila Pharmaceuticals
Probably we need to revitalise such programmes and make them truly successful as we embark on a journey of innovation through better drug development practices. Thus, as the industry evolves and matures, even as firms compete with each other for dominance and leadership positions, collaborations are the way forward for true progress. It is becoming imperative for the life sciences industry to present a united front in the face of heretofore unwitnessed challenges. Only by looking beyond mere profits and redefining IP can the industry harness the ongoing advances in science and technology more effectively and seek new approaches to global problems by working with a wide range of stakeholders and translating them into action.