CLINICAL TRIALS MEETS THE SHARED ECONOMY

 

Introduction

A still contemporary issue is the global insufficiency of health care resources worldwide; this situation will get worse due to the aging population [1]. This unmet need emerged dramatically during the ongoing coronavirus disease 2019 (COVID-19) pandemic [2], [3]; since the beginning of the outbreak, also the world’s richest countries faced resource shortages, including medical workers, personal protective equipment, and ventilators [4]. The lesson learned from the COVID-19 outbreak, and health economics studies carried out in the last decades, suggest applying a shared economy model to the health care industry, as a possible approach to resolve, or at least to alleviate, the health resources scarcity [5]. The shared or sharing economy is an economic concept defined as a peer-to-peer based activity of acquiring, providing, or sharing access to goods and services that is often facilitated by a community-based online platform [6]. Over the past few years, the sharing economy model has rapidly increased and is now used as an all-encompassing term that refers to different types of online economic transaction, including business-to-business interactions [6]. Created in March 2009, Uber Technologies Inc. is an app-based transportation company headquartered in San Francisco, California. It is present in about 270 cities and more than 60 countries worldwide, it is currently worth over $50 billion and is considered one of the major representatives of the sharing economy [7]. Conventional medical services providers are now facing a challenge analogous to that handled by traditional taxicabs after Uber created the new marketplace [5]. The challenge to be faced is how to compete and integrate with a connected services platform that could totally change the current, structured, and licensed  service providers [5].

Through telemedicine and telehealth platforms, the sharing economy has entered the market for medical care delivery, both challenging and completing the traditional modes of delivery [5]. Telemedicine refers to the use of information and communications technology to make available health care services when the physician and the patient are not physically present with each other [8]. Telemedicine is much more than a single technology; it is part of a global process or “chain” of care. This innovative approach could also be defined as a tool that makes healthcare more accessible, cost-effective, and ameliorates patient involvement. It is essential to make a distinction between two concepts: telemedicine and telehealth. Although these words are often used interchangeably, there is for sure a difference between the two terms. The World Human Organization (WHO) refers to telemedicine as “healing from a distance”, meaning the use of telecommunications technology and information technologies to provide distance clinical services to patients. Physicians can use telemedicine for the transmission of digital imaging, video consultations, and remote medical diagnosis. Telehealth is related to the use of electronic information and telecommunications technologies to support and promote long-distance clinical health care, patient and professional health education, public health, and health administration. The main difference lies in the fact that telehealth also covers non-clinical events like administrative seminars, continuing medical education, and physician training. 

Thus, the advent of telehealth denotes a new frontier of the sharing economy, working together and challenging traditional members in the medical care delivery market [5]. The entry of telemedicine platforms into the healthcare market has been subject to strict regulations and competitive limits, including the need to attract both patients and clinicians [5]. Although telemedicine is associated with many possible benefits, there are still some limitations to it as well as hurdles that prevent a wider use. Many players in the market field, such as payers, and policymakers know that there are still some “grey” areas to contemplate. Significant barriers to a wider use of medicine are represented by incomplete reimbursement for the ones who use it, absence of comfort with telemedicine technologies by patients and providers, and few convincing cases for the substitution of in-person care [9], [10]. Considering these hurdles, in recent years, the use of telemedicine has been incremental, but used by only 8% of Americans in 2019 [11]. Furthermore, definitive evidence of the usefulness and cost-effectiveness of telemedicine is still lacking [12], [13], or inconclusive [14]. Hence, currently, only a few telemedicine applications can be recommended for extensive use [8]. Further investigation in this area is definitively needed. Regardless of these limits, and considering the opportunities linked to telemedicine, many healthcare systems are financing to build a telemedicine system, foreseeing a future in which it would become more global [9]. Telemedicine has been studied in multiple clinical settings, demonstrating at least equivalency to in-person care and high levels of patient and health professional satisfaction.


How clinical trials meet the new economy

Many healthcare providers and healthcare stakeholders nowadays are trying to figure out how clinical trials will be designed after the pandemic. As anticipated, the recent COVID-19 outbreak highlighted and speeded up the need to put it into practice the innovative approaches studied and developed in recent years, but still in an experimental shape. Many organizations are already trying to add these approaches into their upcoming clinical trial pipelines [15]. 

In this paper we will discuss the new frontiers in clinical trials, particularly we will focus on how the new sharing economy meets the development of the clinical trial.

Although the sharing economy is a relatively recent concept, especially in healthcare, somehow clinical trials have long been a shared economy since pharmaceutical companies depend on a network of technology skills, research sites, and study participants that they do not own, employ or control [15]. 

As stated in the introduction, telemedicine and telehealth represent an important link to connect healthcare and the sharing economy. This can be applied also to clinical trials, as the availability and sophistication of mobile health technology, including wearables, mobile technology, and sensors, continues to increase, representing a great opportunity to transform these tools in drug development [16]. Main concerns about the use of wearables and sensors in clinical trials generally fall into three points: data accuracy, provenance, and regulatory [16]. Comparisons of the data from various consumer and commercial-grade wearables demonstrate variability among devices related to body placement and other factors [17]. Implementing mHealth technologies into cancer clinical trials could transform and drive oncology drug development and precision medicine to keep pace with the rapidly increasing developments in other fields, such as genomics and immunology [16].

Another significant step forwards in the shared economy in drug discovery has been the adoption of master protocols, which is a unifying study paradigm that includes multiple subgroups and sub-studies, with patients suffering from the same or different diseases and that employ one or multiple drugs to treat it [18]. Originally designed for clinical trials in the field of oncology, master protocol trials are designed to simultaneously evaluate more than one investigational drug and/or more than one tumor type within the same overall trial structure [18]. This was the case of the unprecedented approval in 2006 of Novartis’ Imatinib Mesylate for five new indications based on a single-phase 2 clinical trial [19]. In this first case, the Food and Drug Administration (FDA) not only approved a drug without the habitual two pivotal phase 3 trials, but the same medicine has also been assigned to treat several neoplasms (one solid and four hematologic) [19]. The Novartis’s Imatinib story is a great example of a biomarker-driven precision medicine trial designed using the philosophies of master protocols [18] and leads to the increasing use of master protocol trials in the drug discovery processes, highlighting the growing need for targeted therapies for severe clinical conditions, genomics, and personalized healthcare. As of the high complexity of these trials and the possible regulatory impact, such trials must be well designed and well-conducted to guarantee patient safety and at the same time to get quality data that could lead to drug approval. The main advantage of using master protocols lies in the capability to use a single infrastructure, trial design, and protocol to simultaneously evaluate multiple drugs and/or disease populations in multiple studies, thus speeding the drug development procedure, making it more resourceful [18].

The Draft Guidance for Industry Master Protocols [20] provides recommendations on this kind of study design and conduct. Master protocols may include specific design characteristics that require special considerations.  Examples of types of master protocol design include trials commonly referred to as “basket trials” and “umbrella trials”. Basket Trials include a single investigational drug or drug combination that is analyzed across multiple cancer populations defined by disease stage, histology, number of prior therapies, genetic or other biomarkers, or demographic characteristics [21]. It is usually designed as a single-arm, activity-estimating trial with an overall response rate as the primary endpoint. Significant results in a sub-study could lead to an expansion to generate data that could potentially support a marketing approval [21]. The umbrella trial is designed to evaluate multiple investigational drugs administered as single drugs or as combination drugs in a single disease population. Sub-studies can include dose-finding components to detect safe doses of an investigational treatment combination before proceeding with an activity-estimating component [21]. Adaptive Platform Trials (APTs) use multiple treatments for a single disease, with these treatments allowed to enter/exit based on a decision algorithm. APTs trials have some similarities with umbrella trials in that a single condition is usually studied through multiple interventions. However, in contrast to umbrella trials where all the subgroups go the initial predefined distance regardless of the outcome, in APTs the information created early in the trial is used to adjust its subsequent flow [18]. The main tools utilized by APTs include the use of response-adaptive randomization (RAR) rules to preferentially assign interventions that perform most favorably, rules to trigger the addition or termination of a study arm, or rules to transition from earlier study phase to later phase. As data accumulate from enrolled patients, they are used to real-time update a pre-specified model. The updated results of the model trigger thresholds for the end of an experiment and provide updated randomization instructions for the current APT [18]. 

The draft for Industry Master Protocols Guidance document [20] also defines further characteristics of master protocol designs, trial conduct, and related considerations, such as biomarker co-development, statistical analysis, safety considerations, and master protocol content. It provides advice on how sponsors can interact with FDA to facilitate an efficient review. It also explains the challenges linked to the conduct and analysis of master protocols, such as concerns with assessing the rapidly emerging safety profile of investigational drugs. FDA strongly encourages sponsors to develop drugs under a master protocol with the clinical review partition early in the development program to obtain feedback on the design of such a protocol before submission [20]. 

Following the fundamental achievement obtained in the oncology field, master protocols emerged as important tools providing important answers on what will be the safest and most effective treatments for COVID-19. If master protocols prove their value in this disease, the information and practice acquired with it could speed up and facilitate the trial design process for another drug development after the crisis will be over. For COVID-19 therapies, the focus is on APT trials, which evaluate multiple therapies in a single population with a single standard of care control arm [22]. Considering the severity of COVID-19 and the lack of approved therapies, master protocols emerged as the best route for drug discovery against coronavirus, since they can provide critical information to regulators and physicians trying to analyze and aggregate the huge amount of data from small, non-controlled studies [22]. Currently, there are five master protocol trials understudy for COVID-19 using APTs trial designs, meaning agents can be added and dropped at interim analyses [22]. The still ongoing worldwide crisis will certainly highlight how central these trials are for infectious diseases. The possibility to create common protocols across the United States or, better, globally, would improve knowledge in clinical trial design, ameliorating the drug approval process.

In conclusion, master protocols offer an authoritative new approach to drug development introducing the concept of flexibility and creativity in a highly regulated sector as the clinical trials one. As described, they can be seen as a central tool to incorporate biomarker development, genetic subtyping, and therapies with different mechanisms of action [18]. In other words, they are an opportunity to effectively speed up the development and delivery of new treatments across several therapeutic areas. The main benefits consist thus in time and cost-saving, and continuous learning and sharing of real-world evidence. In this new scenario, researchers can collaborate with other investigators to collect observational data, create natural history cohorts, and quickly test clinical hypotheses. From the patients’ perspective, master protocols offer patients personalized treatment driven by their genetic subtype and biomarker makeup [18]. By using master protocols, placebo exposure could be reduced from the usual 1:1 ratio to 1:5 or even 1:10 [18]. Moreover, nonresponding patients could receive more than one treatment, with consequent more opportunities than before. Finally, master protocols can help patient advocacy groups to hasten the translation of preclinical research into novel treatments for the patient groups they represent. Despite the widely acknowledged benefits associated with master protocols and the FDA's interest and suggestions, there is still some hesitancy in using these models on a wider scale, mainly as of their relative complexity, the concerns about cost and funding, and competition between pharmaceutical companies [18].

Besides master protocols, the sharing economy could meet clinical trials with another approach, this is the “all-comer big-data observational studies”, such as the NIH’s All of Us or Google/Verily's Project Baseline [15]. These studies are open to most all American population and are enrolling a huge quantity of participants, each sharing multiple data from different sources, such as electronic health records, molecular profiles, self-reported, as well as sensor-derived data [15]. 

Another example is the use of sharing economy in clinical trials is based on providing medical equipment through a model of ‘access instead of ownership’. Boston-based technology startup, Cohealo, is allowing hospitals and health systems to share medical equipment across facilities, so they can optimize instrumental use, avoiding wastes.




References

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