Modern healthcare is fundamentally dependent on a constant supply of known and new drugs, making their discovery and manufacture a profitable business. The Indian pharmaceutical industry plays a key role in making drugs available globally at low prices, reflected in its projected revenue of about $130 billion by 2030. However, it largely manufactures generics that target diseases with sizable patient populations. Generics are ‘copies’ of drugs that were under patent protection, but are no longer so. The manufacturer does not have to develop the drug from scratch, although some studies are required. The industry is reluctant to invest in new molecules, particularly for rare diseases, due to the prohibitively high cost of R&D, which can vary from $100 million to a billion dollars, and the limited potential of profit from small patient cohorts.
It is, therefore, essential to reduce the cost of drug development in order to lower the price of drugs and encourage the manufacture of new drugs. The government can play a key role here in several ways.
Simplifying regulatory frameworks
In India, drugs cannot be manufactured or distributed unless approved by the Central Drugs Standards Control Organisation (CDSCO). Several steps must be followed for approval, including preclinical studies, multiple phases of clinical trials, and post-approval clinical studies. For each stage, specific requirements are laid out by CDSCO and these are governed by the New Drug & Clinical Trial (NDCT) Rules, 2019. Drug sponsors must comply with these requirements, and the paperwork can be overwhelming. Limited preclinical and clinical studies are required even to obtain approval for manufacturing generics. Simplifying the drug approval process, coupled with cost reduction, is essential to encourage companies to engage in more new drug discovery in India.
Boosting AI and non-animal approaches
Preclinical studies contribute to a substantial portion of the time and cost of drug development. There are three significant steps in preclinical development. Efficacy studies are typically conducted using animal models intended to mimic human diseases. These studies are costly and time-consuming, and suitable animal models are often unavailable for many diseases (particularly rare genetic disorders). Globally, including in India, there is now an emphasis on the use of cellular (stem cells, organoids) and computational models. It is possible to create banks of stem cell lines from patients for an array of diseases. These cell lines can then be transformed into tissues and organoids suitable for efficacy studies. Additionally, animals are routinely used in toxicity studies, and NDCT-2019 recommends using two different animals to determine toxicity. Standard laboratory animals, such as rodents, do not always replicate the effect of the drug seen in humans. Recent advances in artificial intelligence (AI) have enabled the development of virtual methods for toxicity assessment, accelerating preclinical development. Non-animal approaches for Pharmacokinetic (PK) and Pharmacodynamic (PD) studies are increasingly replacing traditional in vivo (animal) models. These methods focus on human-relevant systems (such as cell lines and organoids) and computational modelling, but need a leg up in India to be able to bring down costs.
Adapting new trial designs
The total cost of clinical trials for a given candidate drug can range from a few million dollars to hundreds of millions, depending on the drug type, targeted disease, number of participants, and potential complications. These costs can be broadly categorised into the design, and the execution costs. The most significant individual cost components are typically site management and investigator fees, and patient recruitment and retention expenses. Generally, standard trials require recruiting large numbers of patients across multiple sites to achieve high statistical power. Also, they often involve costly investigations. For rare diseases (including some cancers), patient cohorts are likely to be small, making it difficult to recruit sufficient patients, but reducing the cost as well as discriminatory power.
Recent innovations in clinical trial design are helping to reduce the cost of trials as well as assisting in conducting meaningful trials. These include:
Patient-centric trial designs: These focus on patients’ responses and their well-being rather than just traditional endpoints such as overall survival or progression-free survival in the case of cancer patients. Importance is given to the quality of life as perceived by the patient. Considerable clinical data can be collected through patient-reported outcomes (PROs) at a much-reduced cost. Many regulatory bodies, such as those of the U.S. and Europe, are encouraging the inclusion of PROs in trial designs.
Adaptive trial designs: These are flexible trial protocols that allow modifications during the course of the trial based on interim results, without undermining the study’s validity. This approach is highly beneficial in rare disease trials, as it reduces the number of patients required, shortens trial timelines, and increases data-generation efficiency.
Master protocols such as basket and umbrella trials allow the evaluation of multiple treatments within a single trial, reducing costs and effort. Since many rare diseases display patient-specific symptoms, “n” of “1” trials (a clinical trial conducted in a single patient where the patient serves as their own control) are being recommended, which allow data to be generated using very few patients. Many regulatory bodies are also promoting the use of surrogate endpoints (a substitute for a direct measure of a clinical benefit) in several diseases where traditional endpoints cannot be achieved in a trial. For many trials, the need for a placebo as a ‘control’ can be avoided by using real-world data from patient registries or natural history studies, further reducing costs and time.
Finally, AI has become an essential tool to design and implement various trial designs. Many regulatory bodies are allowing the use of AI in different phases of the trials for better prediction and monitoring.
These trial designs and approaches could go a long way towards reducing costs and encouraging pharma companies to invest in the research and development of new drugs, especially for rare diseases.
The path ahead
India needs to make a conscious effort to simplify its regulations incorporate and lay down guidelines for innovative trial designs and allow for the safe use of AI. These practices are already being followed in a number of countries. Changes need to be made to the NDCT rules, and these coupled with the Orphan Drug status provisions (Rule 101) that allow for a waiver of local clinical trials if a drug is approved in specified countries (U.S., UK, Japan, EU, etc.), could go a long way towards making drugs for rare diseases accessible and affordable for the many patients in India.
(Alok Bhattacharya is honorary professor of biology, Ashoka University; Dr. Rakesh Mishra is director, Tata Institute for Genetics and Society, Bengaluru and Gayatri Saberwal is a consultant, Tata Institute for Genetics and Society. alok.bhattacharya@gmail.com)
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