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Genedata Profilerによるマルチステークホルダーコラボレーションが可能にする細胞治療開発

July 19, 2022
Justyna Lisowska

In the last decades, biopharma organizations have been increasingly partnering with a wide range of stakeholders to better address scientific, technological, and regulatory obstacles hampering R&D productivity. Pre-competitive collaborations including joint ventures and consortia with academic or governmental institutions are common and have already demonstrated their value in multiple areas of public health (e.g., in immune-oncology, neuroscience, or cardiovascular diseases). But the willingness to share technology, scientific expertise, and data across organizations, goes beyond public-private partnerships and is continuously being propelled by:

  • a growing number of unmet patient health needs,
  • increasing biological complexity of previously unexplored diseases,
  • the emergence of new therapeutic modalities and technologies used, and
  • the amount and variety of data generated.

Nevertheless, to realize the full potential of this open innovation approach, collaboratively advance research questions and spur innovation in society’s most pressing healthcare issues, innovative digital infrastructure, and cloud-computing solutions, like Genedata Profiler®, need to be incorporated within the biopharma ecosystem.

Cell Therapies and their Challenges

Cell therapies represent a nascent field of therapeutic modalities with an unprecedented level of biological, technical, logistics, and regulatory challenges. Originating from academic research, these transformative treatments have witnessed impressive clinical development in the last few years. As shown by ClinicalTrials.gov, as of April 2022 there were approximately 1800 active cell therapy trials. Nevertheless, despite fast advancements in the field exemplified by the recent FDA approvals and continuous R&D investment, these therapies continue to face steep hurdles in reaching the market at scale. Why?

As highly personalized medicines designed for short-term treatment and curative outcomes for a small group of patients, cell therapies are associated with highly sophisticated, lengthy, and expensive development processes and complex logistics. The unique biological nature of these advanced therapeutic medicinal products gives rise to specific challenges. Unlike off-the-shelf blockbuster therapeutics, these living drugs display intrinsic high variability in response to their surrounding environment. Therefore, the process of developing such a therapeutic product through in vitro manipulation (genetic modification, cell expansion, etc.,) is extremely complex and sensitive. Besides, since their efficacy and safety depend immensely on how well they integrate with a patient’s body, it is difficult to run normalized tests in advance which limits product standardization. In addition, these advanced medicines vary substantially in terms of their provenance (donor), cell type used, and technology applied to modulate the target function. A high level of heterogeneity may also exist between product batches. As a result, determining objective quality attributes ensuring product safety and efficacity and thus, providing clear go/no-go decision criteria for large-scale development remains extremely challenging. Moreover, despite potential efficacy, these therapies are sometimes accompanied by life-threatening adverse events. To ensure product safety, regulatory bodies require monitoring of the patient's journey during treatment and for 15 years after. This entails lengthy clinical trials and/or real-world evidence studies. Such trials not only generate high costs, unsustainable for small companies developing such innovative medicinal products but are also associated with the burden of management and analysis of vast amounts of complex trial data which serve regulatory authorities for product evaluation. Finally, due to the personalized nature of cell therapies and their extensive vulnerability, companies must oversee the whole product life cycle from the raw material collection at the clinic, through laboratory production until its delivery to the patient at the treatment center. This requires a high level of diligence, enhanced coordination, and cooperation between multiple stakeholders and disparate sites.  

The New Trend of Open Innovation

The complexities underlying the discovery, development, and manufacturing of cell therapies are beyond the ability of any one organization or sector to succeed alone. Therefore, more and more often, companies seek to collaborate to resolve challenges and progress faster. Public-private partnerships are common and lie at the heart of successful translation of research into a marketed product and are examples of a mutually beneficial exchange. While academic institutions fuel innovative ideas and provide scientific expertise, biopharma brings the resources and knowledge needed to run large clinical trials, engage with regulatory agencies, and scale-up manufacturing. However, the thirst for outside know-how and resources to gain operational efficiencies and speed up the laborious development and manufacturing process pushes companies to establish alliances with other external organizations.

As research centers, many small biotechs developing cell therapies are not equipped enough with all the technologies, operational infrastructure, and/or knowledge needed to address all the development-related bottlenecks and take their asset to the market. To do so, they either outsource part of their development/manufacturing work to external organizations such as CROs and CDMOs, undergo mergers and acquisitions by larger, more mature companies, or establish different collaboration agreements. Pharma organizations are considering each other no longer as fierce competitors but as allies. This is because working in a collaborative ecosystem empowers the biopharma industry to innovate in a cost-effective and timely manner helping to achieve common goals and overcome existing R&D and manufacturing challenges more efficiently. Thoughtful partnerships also allow for creating a more harmonious and standardized clinical development process and help to define common quality standards within the biopharma community accelerating regulatory approvals. The value of knowledge and resource transfer across pharma organizations has been well exemplified during the global Covid-19 pandemic. Pfizer, BioNTech, and Sanofi have been working together to rapidly develop and deploy efficient solutions to end the healthcare crisis. Such inter-organizational collaborations are perpetuating across cell therapies as well. An example of such a collaboration is Century Therapeutics and Bristol-Myers Squibb (BMS) working together on four induced pluripotent stem cell (iPSC)-derived, engineered natural killer cell (iNK) and/or T cell (iT) programs for hematologic malignancies and solid tumors. Moderna and Carisma Therapeutics Inc also collaborate on engineered chimeric antigen receptor monocytes (CAR-M) for the treatment of cancer.

Digital Transformation to Foster Cross-Organizational Collaboration

While cross-organizational collaboration seems no longer to be a threat but rather a new business imperative in the increasingly complex and challenging biopharma landscape, the promise of open innovation can only be realized if a cultural shift is accompanied by digital transformation. Digital tools have the potential to break organizational silos and streamline cooperation by improving data curation and facilitating data sharing. But how can we enable efficient knowledge transfer across collaborating organizations while maintaining data security and privacy? Companies may want to work together on a specific project, but they certainly do not intend to reveal all the secrets of their work.

Genedata Profiler, a state-of-the-art cloud-based platform for translational research, has been purposely designed to streamline multi-stakeholder collaboration while maintaining a high level of data security. The software enables a diverse group of people, with different roles and responsibilities, to work autonomously on joint projects by providing the right users with the right data and tools needed to perform their respective tasks, while restricting access to sensitive data by unauthorized individuals. This is ensured through study-based data organization that allows centralized access to data available for sharing. A study is the virtual project-related space within Genedata Profiler, where partners can store relevant data, workflows, analyses, etc. Within a study, all items are well-organized in a folder-like structure so that all project members can easily find whatever they need to work efficiently.

To improve data organization and discoverability, Genedata Profiler requires all data to be correctly annotated with consistent metadata across all files within the study. This allows collaborating organizations to establish standardized nomenclature facilitating communication while enhancing interoperability. Finally, each study has project members assigned with defined data access and data handling activities through specific role-based permissions. Only study users are authorized to benefit from the data and functionalities of the software to perform their tasks. In addition, Genedata Profiler ensures all imported and stored data is tracked and the data-handling activities of the respective users are logged and saved. Finally, to reinforce the safety of the system and prevent data corruption, every user needs to log in with their credentials and authenticate their identity with a secondary personal device every time they access the platform. This not only improves system security but also provides flexibility. By allowing any portable device to connect with the virtual data source in a safe manner, project members can be easily onboarded and can work productively on available data from any location without the need to go on-site or connect to any physical machine to up/download files. This is particularly useful for partners spread across the globe collaborating on short-term projects. In addition, the dedicated Profiler e-learning platform with a variety of courses specifically tailored to the needs of different user types, allows them to become productive much faster and optimize their use of the system. Upon project completion, when users need to leave, they can be easily and securely offboarded through deactivation of their user rights in Genedata Profiler, while the data remains in the platform.

In addition to data, Genedata Profiler provides its users with centralized, self-service access to a wide range of analytical tools. This is ensured through its embedded superior interoperability with external analysis systems (such as RStudio, Tableau, PowerBI, etc.) and enables multiple stakeholders to access, directly from Genedata Profiler, the applications of choice to efficiently progress common projects. The extended dashboard building capabilities with automated data updates also allow for generating and sharing insightful data visualizations seamlessly. This way, the progress of projects can be monitored in real-time and informed decisions can be made quickly.

Improved dialog and cross-organizational cooperation can be a real game-changer to advance the development and streamline the path to regulatory approval of complex therapeutic modalities like cell therapies. Yet, to support a collaborative approach in a regulated and highly protected environment, a high-performance digital infrastructure is needed. The improved virtual connectivity, high level of security, instant availability of data and tools, and reduced IT complexity as well as a self-service e-learning experience provided with the software, make Genedata Profiler the ideal environment for partnering organizations to collaborate safely while advancing the development of new transformative treatment.

Foster Collaboration with Genedata Profiler