[Part I] The Trial of Data Exclusivity
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With reports suggesting that the Organization of Pharmaceutical Products in India is pushing for up to 10–12 years of data exclusivity protection in India, the debate over affordable medicines and pharmaceutical innovation is once again gaining momentum. But what would such a regime mean for India’s carefully negotiated patent bargain, generic competition and access to medicines? In Part I of the three-part post, Arnav Kaman examines the parallels between patent protection and data exclusivity, and the important questions that the proposed framework raises. Arnav is a 5th-year law student from Rajiv Gandhi National University of Law, Punjab. He’s interested in Narratives and the Law.
[Part I] The Trial of Data Exclusivity
By Arnav Kaman
The Organization of Pharmaceutical Products in India (OPPI) has reportedly been pushing to introduce a data exclusivity framework for clinical trial data of new drugs. OPPI represents the interests of multinational big pharma innovator companies, and have publicly stated their desire for a regulatory data protection (RDP) framework for years now. In recent reports, it’s been stated that the industry body is seeking a 10-year protection period for New Chemical Entity and 12 years for Biologics beginning from the date the drug receives marketing approval in India. The Indian Government seems to be taking steps towards it behind closed doors, in the name of increasing investment. While the exact proposal is not out, it’s a good time to revisit and contextualise the debate regarding Data Exclusivity for Pharmaceuticals. Part I will analyse the parallels between the Data Exclusivity proposal and the Patent Bargain, Part II will consider the impacts this proposal will have across multiple policy dimensions, and Part III will conclude by providing some alternative treatment.
Some Context and Background:
At the very outset, it is important to clarify some of the terms used in this fight, as they can be used interchangeably but imply vastly different things. When clinical trial data proving the safety and efficacy of a new drug has been generated and submitted, and a subsequent applicant applies for approval, rather than forcing duplicative trials for subsequent applicants, the approving authority relies on the pre-existing data to prove safety and efficacy. Regulatory Data Protection (or RDP) is the umbrella term for various policy measures and frameworks that protect this clinical trial data. Data Exclusivity refers to the framework where the authorities will not allow reliance on the submitted clinical data for approving subsequent applications. Market Exclusivity refers to the restriction imposed against competitors from entering the market with a competitor product for a period of time. Lastly, Data Confidentiality refers to the maintenance of confidentiality of the clinical trial data and preventing unauthorized disclosure.
These distinct terms can be made clearer with an example of the EU Exclusivity framework wherein they implement the “8+2” system [Article 14 (11) of Regulation (EC) No. 726/2004]. Data Exclusivity is granted for eight years after market approval for innovator products, wherein authorities cannot rely on the innovator trial data for approving generic or biosimilar products. Market exclusivity is granted and runs parallel from the date of marketing approval for ten years. Thus, for the last two years, even when data exclusivity runs out, approved generic or biosimilar products cannot enter the market.
India, on the other hand, does not currently provide for a data exclusivity regime. The New Drugs and Clinical Trial Rules, 2019 provide the requirement for new drug approvals and clinical trials. But after a “new drug” is approved with sufficient clinical trial data, for subsequent applicants the NDCTR provides instances wherein a requirement for local clinical trial data is waived off through Rule 80(7) and Rule 101. India does however, maintain confidentiality of the trial to adhere to TRIPS Article 39.3, as our international obligations mandate.
It is in this context that OPPI is asking for the introduction of a 10-year protection period for NCEs and 12 years for Biologics beginning from the date a drug receives Indian regulatory approval. Their proposal has faced push-back from generic companies and reportedly also the Health Ministry, raising concerns about access and delayed generic entry. OPPI has rebutted this, stating that generics should be able to generate their own safety and efficacy dossier. Further, OPPI argues that having strong DE style protection will lead to increased investment in clinical trials in India. Let’s unpack exactly what this proposal entails by first examining its parallels with the patent system and the greater impact it will have in India across different dimensions.
Phase 1: The Patents and Data Exclusivity.
The basic premise for data exclusivity is that undertaking the required costs for new drugs is an extremely high-risk and costly activity, which needs to be sufficiently incentivized by providing exclusive protection. Sound familiar? Yes, because it’s almost the same premise that’s led to the patent system. But if patents already exist in pharma, then why do some believe it is not enough? The answer lies in the clinical trials themselves, which are highly cost-intensive procedures, and since patents do not directly cover the investment in generating the data but only the end product, a patent alone does not sufficiently incentivize the production of such data. Or so they claim. Comparing the data exclusivity proposal with the patent bargain is a useful exercise and reveals many curious gaps and lacunas.
Firstly, as noted by Swaraj and Sabeeh, while no doubt there is a non-trivial amount that goes into conducting clinical trials, there is a staggering lack of transparency as to the actual costs of the drug development process. The transparency question does not end only at costs, but also extends to the data itself. The patent bargain operates without knowing the costs of the R&D, but justifies providing protection due to the trade-off of the knowledge of the innovation being publicly disclosed in exchange. The data in clinical trials, however, remains a secret in perpetuity and is not revealed to the subsequent applicants or the public at any point. Without knowing how much investment took place in the first place or how useful the information is, it is difficult to approximate the level of incentive required for innovation. Conversely, given the amount of discussion around how AI may be reducing time and effort in creating new drugs, it may be a prime moment to re-evaluate whether the patent period itself is properly ‘balanced’ or not! Of course, this should be done by making the relevant economic data public, and not by asking pharmaceutical companies whether they need more market power or not.
Secondly, DE has no standard of scrutiny unlike patents. The patentability standards of novelty, inventive step, and industrial applicability exist to ensure only “true” or rather “substantial” “innovation” is granted protection. In pharmaceutical patenting, there are also the additional burdens of Section 3(d) and therapeutic efficacy, which all go a long way to prevent ever-greening of medicines. Data Exclusivity, on the other hand, possesses none of these safeguards and the approval process shares little in common with patenting standards. Further, any incremental innovation, subsequent improvement on any existing drug, could also be granted new data exclusivity periods. In both the US and Europe, incremental innovations have been granted data exclusivity periods, effectively ever-greening certain products. It’s possible that even if a product’s patent term expires, the data exclusivity may not only continue but be extended due to an incremental innovation! Yin, in a study comparing gains/losses from this type of activity with regard to SSRI drugs, found that the consumer surplus losses due to market exclusivity extensions far exceed the consumer surplus benefits from incremental innovation. For the Indian scenario, it’s important that safeguards be put into place for the data exclusivity regime to prevent ever-greening in such instances.
Thirdly, there are ambiguities on what timelines and territorial options to opt for. OPPI is pushing for the period of exclusivity to begin from Indian approval, territorially restricting it, but whose interests does it really serve? Would the additional protection of DE only be granted to trials that took place in India alone or anywhere in the world? If, in fact, DE would be granted for trials done outside India, which would then only require bridging trials for Indian approval, why does it require the additional protection incentive of Data Exclusivity in the first place? One cannot allow for waivers of local clinical trials and Data Exclusivity at the same time. While the patent system grants independent terms from the date of filing in each country, there are incentives to file globally simultaneously. If one delays filing in one country, they lose out on priority or novelty of the innovation and thus instruments such as the PCT supplement the ability to file internationally. In data exclusivity, however, innovators have full confidential control over the data and need not worry about fulfilling any time-bound requirements. An independent data exclusivity term might even incentivise a late entry in Indian markets.
Furthermore, the periods being discussed are unusual! What is the logic of asking for 10 and 12 years for NCE and Biologics? In the US, which has some of the strongest data exclusivity regimes, they only grant 5 years of exclusivity for a New Chemical Entity. And as mentioned earlier, the common practice right now is for CDSCO to waive studies or only require bridging studies. So, what exactly are these terms allegedly needed to incentivise? What exactly are we losing out if these are not granted? Let’s remember what comes out when the masks have slipped in the past, such as when Bayer’s CEO stated that Nexavar (which received a Compulsory license) was not made for Indians, but only for Western patients who can afford it. Big pharma is prone to using its monopolistic powers to price out patients, with a number of practices including additional protections such as data exclusivity. These years will be crucial, as claimed, when it comes to appropriate incentivisation of innovation and generic competition, so they must be well substantiated with evidence.
Lastly, we must not forget medicines are ultimately a public good and require state levers to ensure the balancing of private commercial interest with the needs of the public. In the patent regime, this lever manifests in the form of compulsory licensing under Section 84 and 92 of the Patents Act. However, compulsory licensing only removes the patent barrier of a medical product, and generic manufacturers may still be restricted from launching their alternatives in the market because of the lack of safety and efficacy approval. Data that would be locked behind the barrier of the DE regime. Thus, there is a great need for a state lever in the DE regime to ensure public interests.
The Indian Patent Bargain has been developed and has evolved over years and years of consultation, along with trial and error, and all the hard-won trade-offs should act as lessons for the DE regime when it finally reaches our doors. Yet even if and when these lacunae are addressed, the impacts of any DE regime on this country will have grave consequences across many policy dimensions which will be analysed in part II.
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Continuing the discussion on the proposed introduction of data exclusivity in India, in Part II of his three-part post, Arnav examines its potential implications for domestic innovation, access to medicines, foreign investment, and the conduct of clinical trials. He also questions whether data exclusivity would address the underlying challenges facing India’s clinical trial ecosystem, and whether the promised benefits would justify the costs to public health and the domestic pharmaceutical industry.
[Part II] The Trial of Data Exclusivity
By Arnav Kaman
Phase II: The Policy Dimensions of Data Exclusivity
- Innovation
OPPI argues that introducing data exclusivity is the instrumental push required for “incentivising and bringing innovative drugs” to the country. Without a data exclusivity regime, they and other proponents of DE argue there are no substantial incentives for conducting local clinical trials and innovating in India. One account tells us of an instance where an Indian Pharma company’s local clinical data was used for approval by another bigger Indian Pharma company (paywalled). A DE regime would increase domestic investment into conducting our own trials and developing domestic NCEs or Biologics.
Yet, OPPI represents big pharma’s MNCs, and if foreign investment into India from big pharma grows due to protection of clinical data, will there even be space left for domestic innovation to flourish? Irony will have it that, before the TRIPS era, these MNCs of the West flourished partly due to the lack of a data exclusivity regime in their countries. Note that while a DE regime brings in additional protection and reward for the first mover, since there is no disclosure of the data (unlike patents) there is no contribution to the public knowledge or ability of the domestic market from DE. The additional protection of DE will certainly not drastically alter domestic innovation to transition into an innovation hub overnight either. Especially without additional safeguards and incentives for domestic local innovation, the DE regime will not stimulate the field alone.
- Access
The additional protection granted from data exclusivity terms will allow innovator companies to enjoy a safe and long monopoly. During the term of the patent, the likelihood of breaking the patent through litigation or post-grant opposition still exists. But no such mechanism exists to break data exclusivity terms. The only alternative to these medicines would be for generic alternatives to generate their own safety and efficacy data, which in turn would increase the price of the generic drugs, if done.
While the exact figures elude us, it’s clear that generating data for new drugs or biologics is a great capital investment, cost, and risk, which would deter many generics from attempting trials in the first place. On the other hand, for Indian companies that do wade into conducting clinical trials, it would lead to a drastic price increase of generic equivalents of new drugs. Worse, it’s not even clear whether any of the benefits of the innovation would be worth the loss to patient access.
- Foreign Investment
It is well known now that the international community, including both the EU and the US, has attempted to pressure India into implementing a data exclusivity regime through trade deals and bilateral negotiations. India has stood firm for many years, supporting its generic industry against this pressure. While one year of the India-EFTA TEPA was recently celebrated, it’s best to remember that the record of understanding also requires reconsideration of “the issues relating to protection of undisclosed information from unfair commercial use” after one year in force. Big Pharma MNCs (here) have publicly stated their wish for India to “reform” their pharmaceutical laws, introduce data exclusivity, and the government is seemingly conducting many closed-door meetings with these lobbies. It’s also delicate timing, as noted here, that in the next seven years, blockbuster drugs estimated at about 300 billion USD are to go off-patent. Thus, any additional protection they can garner is crucial for such companies maintaining their profits. But the introduction of such additional protection would come at the great cost of patient access, damage to our domestic industry, as well as losing control of our own regulatory autonomy.
- Safety & Efficacy Data/ Increasing Local Trials
Lastly, comes the big question of whether or not data exclusivity would improve the safety and efficacy of drugs. The role of ethnicity seems to have a role in certain instances of drug metabolism and pharmacokinetics, and thus clinical trial investigators must ensure a broad racial representation while developing treatments. For example: Warfarin doses need to be different for each race.
Prashant Reddy had argued that even with the requirements of diversity by regulatory boards, there is a marked lack of the diverse Indian population in clinical trials, which results in the approval of drugs that may not be optimised with our diverse population in mind. Thus, introducing data exclusivity can incentivize conducting local trials and providing for more safety and efficacy data for the specific socio-economic-genetic context of the Indian subcontinent.
This argument, however, is already contradictory when you consider India’s frequent approval of new drugs that have been approved abroad by waiving local trials and only requiring minimal BA/BE trials and bridging studies. Big pharma MNCs are innovating for foreign populations already, and if the mechanism of local trial waivers exists, it is unlikely they will conduct local trials once more in India. As noted in part I, you can’t have data exclusivity and local waivers at the same time. Nonetheless, there’s still a worthwhile question to be considered about the current state of clinical trials in India.
While it is true that Indian populations are woefully underrepresented in certain clinical trials, such as those for rare diseases, it is no longer true that there are, by any metric, too few clinical trials taking place in India. Looking at the global data (here), not only are there a great number of trials here, in fact, but India has also now officially overtaken the US in the number of clinical trials registered this past year. This includes both trials undertaken by Indian pharma companies and MNCs setting their clinical trials in India. But we must be clear as to what kinds of trials are taking place here.
India does not have many early Phase 0 or Phase I human trials (Most Indian companies themselves chose to undertake Phase I abroad). Phase III trials make up the bulk of registered trials here. While Phase I of clinical trials require a smaller set of healthy participants who need close monitoring and specialized facilities for observation, Phase III involves much greater patient populations across multiple hospitals. India, as has been observed by experts, does not have the facilities required for Phase I trials. But then why do both Indian companies and MNCs opt for India for late-phase clinical trials? Why has there been a great rise in clinical trials in India?
Because India has a large patient pool with an abysmally low rate of compensation and lax regulations. The extremely low rate of compensation for injury or death in clinical trials in India have been noted before and lead to the reform of compensation calculation in 2013 along with new guidelines in the NDCTR 2019, which is still riddled with complications. The most pressing of all being that the base amount of 8 Lakhs has not been updated for inflation in the past 13 years! Even with the new changes brought in, deaths in clinical trials are still a common occurrence (here) and their compensation remains contentious especially with the lack of insurance measures. Professor Basheer wrote about how drug companies exploited the lax regulatory standards of the country almost 10 years ago (here) and that continues to be the case. The regulatory oversight burden of compliance with the NDCT Rules and Good Clinical Practice has been passed onto ethics committees, privately established by hospitals or private institutions registered with the CDSCO. It’s not an uncommon practice for these ethics committees not to be doing their duties(!), the CDSCO cancelled the registration of seven ethics committees this July due to non-compliance. This has not deterred the increasing investment of MNCs to conduct clinical trials in India. Bristol Meyers Squibb has invested 100 million dollars in an early stage drug development center in Hyderabad and Roche’s Partnership with the CDSCO is only two examples of an uptick in foreign investment. The data generated in India is not only used for approvals here but is part of a larger multinational pipeline for approvals of new drugs all over the world, so a country where life is compensated cheaply and regulation is lax is already a goldmine.
In light of this, does the country really need DE to incentivize more local clinical trials? The problem facing Indian trials is not one of quantity but that of quality, which DE will be unable to directly affect. If India wants to become a country with not just more clinical trials but specifically more early trials, first we have to manage quality at a smaller scale before we can scale up.
The analysis of these various dimensions and considerations asks the question that must be answered before any policy implementation: Will the trade-off be worth it? There are genuine concerns about the current domestic pharma industry, but data exclusivity need not be the only answer. Part III will examine what alternatives might exist to answer some of these concerns.
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In the third part of the post on data exclusivity (see here for Part I and Part II), Arnav explores whether there are alternative ways to incentivise domestic pharmaceutical innovation and clinical trials without introducing a data exclusivity regime. In this post, he examines possible policy interventions and alternative models, including a compensatory liability framework, while also highlighting the need for meaningful public consultation before any such policy decisions are made. Arnav is a 5th-year law student from Rajiv Gandhi National University of Law, Punjab. He’s interested in Narratives and the Law.
[Part III] The Trial of Data Exclusivity
By Arnav Kaman
Phase III: Alternative Treatment
Not all proponents of the data exclusivity regime are bad faith actors. There are genuine concerns of how to increase domestic innovation and generate safety and efficacy data suited for Indian populations but the question asked at this point must be: Is data exclusivity the best or only model to address such problems? For me, it appears to be a classic case of trying to push a square peg into a round hole. Data exclusivity is thankfully not the only solution.
Outside of direct injection of money into public clinical trial facilities, the government should (and already has) provide for other incentives for innovation such as direct grants and prizes for rare diseases that disproportionately affect Indian populations. Considering how international regulatory bodies require trials conducted with good clinical practices and ethical review, increasing regulatory oversight and enforcement from CDSCO will only likely make the country more attractive for clinical trials when it comes to quality for early phase clinical trials. By focusing on quality first, India can become a proven area for early clinical trials
Beyond these policy measures to supplement the current system, there are alternative regimes such as the compensatory liability model touted by Prof. Basheer in his thesis. The model imagines protecting the investment of R&D made by innovator companies, not by patents or data exclusivity, but rather through a compensatory liability model whereby competitors could enter the market only after paying reasonable compensation to the originator. Rather than relying on market conditions that could take many years for a return, originator companies could gain a reliable fee from competitors. This model consisted of a cost sharing methodology wherein the costs of the drug development process from discovery, capital allocation and clinical trials would be submitted and made public to determine the compensation. Until these total costs and reasonable return would be accrued by the originator wherein this period of “exclusivity” would then end.
This model would require a degree of financial transparency as originators would submit the exact costs accrued for the clinical trial for formulation of the appropriate compensation. It would not only sufficiently incentivize trials, but also avoid the drastic impacts that a DE regime would have on the domestic industry. All it would require is a little bit of honesty and co-operation.
On a final note, I want to take a moment to point out that we, the public, essential stakeholders have only come to know of these recent rumblings of data exclusivity from third party sources such as news reports and LinkedIn posts. We know that closed-door meetings between the government and MNCs and pharma lobbies took place after last year’s CSDSCO notice but we remain in the dark about the exact directives planned. No statement has been tendered by the government declaring their newfound considerations nor has there been a public call for consultation specifically about the regime of data exclusivity, the date of approval, the period of time, etc. Public consultations only seem to take place after the decision has been made and we are called forth only to discuss how to cross the t’s and dot the i’s. The irony of all of this is that Public Consultations and Clinical Trials actually share the same common premise: Solutions that affect everyone must account for everyone. Before any decisions to introduce data exclusivity are made, we must be sufficiently consulted. Otherwise, we will all have bitter pills to swallow at the end of this road.
(The Author would like to thank Swaraj and Praharsh for their unlimited patience and deeply insightful contributions to the post, and Archi Chaturvedi for her valuable insights)