Medidata Drives Clinical R&D Transformation Through AI and Digital Innovation, Collaborating with 2,300 Pharma Partners

Recently, Medidata China, a provider of clinical trial solutions for the life sciences industry, successfully held its annual “NEXT China Conference” in Shanghai to mark its 10th anniversary.

The annual conference, themed “Advancing with the Times, Intelligently Embarking on a New Journey,” highlighted how Medidata Experiences leverages digital intelligence to drive innovation in clinical trials and transform the entire R&D lifecycle from development to commercialization.

The conference featured three themed sub-forums: “Data and Patient Experience – Patient-Centric Clinical Data Governance,” “Research Experience – Quality by Design and Excellence in Clinical Operations,” and “Leading the Future of Pharmaceuticals and Medical Devices – Deepening R&D, Safeguarding Quality.”

Meanwhile, to advance the implementation and practical application of innovative technologies, Medidata has also launched “Innovation Space” and “Hands-on Practice and Demonstration Sessions” this year, helping users integrate new technologies into their workflows more quickly.

As can be seen, Medidata’s collaboration with Chinese life sciences enterprises has further deepened in recent years. According to data disclosed by Medidata, as of the end of July 2025, Medidata had partnered with nearly 550 sponsors and more than 80 international and domestic CRO partners in China, cumulatively supporting nearly 3,000 clinical trials with approximately 450,000 patients enrolled.

Ms. Li Wei, Vice President and General Manager of Greater China at Medidata, stated at the conference: “This year marks the 10th anniversary of Medidata’s establishment in China. Embracing the spirit of ‘Advancing with the Times,’ we will leverage digital intelligence to embark on a new journey, further deepen our strategic layout in China, expand the boundaries of collaboration, and help build a smarter industry ecosystem. We aim to empower local innovation breakthroughs and global expansion for enterprises in China, ensuring that the fruits of innovation ultimately benefit patients worldwide.”

Today, the sources for collecting patient data are more abundant than ever before. However, to efficiently integrate and manage this data, leverage data analytics to uncover precise decision-making insights, and thereby enhance the quality and efficiency of clinical trials, AI may be the only viable solution at present.

Therefore, as an innovator in the digitization of clinical trials and AI technology innovation, Medidata is progressively integrating AI technologies comprehensively into the unified Medidata Platform. This strategic shift moves from point solutions to a model driven by three core experiences—patients, data, and studies—leveraging digital and intelligent innovation to drive transformation in clinical development.

This is precisely the core proposition of Medidata Experiences. As stated by Joe Schmidt, Chief Operating Officer of Medidata, and Lisa Moneymaker, Chief Strategy Officer of Medidata, in their keynote address, Medidata Experiences primarily focuses on three key experience domains: patients, data, and research. By leveraging intelligent collaboration to enable a more unified and integrated trial paradigm, it aims to optimize the end-to-end patient trial experience, seamlessly connect and manage multi-source data, thereby accelerating the R&D process and addressing more unmet patient needs.

Specifically on the data front, Medidata aims to break away from traditional clinical trial paradigms, revolutionize the patient experience, and enable data collection across the entire patient journey, while also expanding data sources to provide more comprehensive and robust data support for clinical research.

Through the Medidata myMedidata application, patients can remotely participate in clinical trials from home by entering data via a mobile app. Furthermore, Medidata is simultaneously exploring the value of wearable technology; patient data continuously collected through sensors provides researchers with a more real-time and comprehensive view of patient status. Such data, characterized by its continuity and multidimensionality, extends to various aspects of patients’ lives and serves as a robust complement to subjective data such as patient-reported outcomes.

As data volumes increase, Medidata also leverages AI to automatically verify all data collected during trials, thereby enhancing efficiency and reducing the burden on data managers. During trial execution, Medidata AI can make predictions based on historical clinical trials, helping sponsors identify suitable investigative sites and classify the hundreds or thousands of documents generated throughout the trial.

Revisiting the Patient Side. Many clinical trials face challenges such as high patient dropout rates and inefficient data processing. To break this impasse, Lisa Moneymaker regards “patient experience” as the core solution. She believes that the best way to enhance patient experience is to engage patients deeply in clinical trials, working together with sponsors to identify and address issues across the entire lifecycle.

Certainly, sponsors also need to upgrade the tools used in clinical trials. To address this issue, Medidata has widely adopted technologies such as DCT (Decentralized Clinical Trials), which not only reduce the burden on patients participating in clinical trials but also effectively enhance their sense of involvement and overall experience.

Focusing on specific clinical trials, a collaboration between Bristol Myers Squibb (BMS) and Medidata may demonstrate the value of AI in clinical trials.

In March 2024, the U.S. Food and Drug Administration (FDA) announced the accelerated approval of Breyanzi (lisocabtagene maraleucel; liso-cel), the first CAR-T cell therapy developed by Bristol Myers Squibb (BMS) for the treatment of adult patients with relapsed/refractory chronic lymphocytic leukemia (R/R CLL) or small lymphocytic lymphoma (SLL). This breakthrough provides a new therapeutic option for patients who have received prior treatment with both BTK inhibitors and BCL-2 inhibitors.

CLL and SLL are common leukemias in adults, typically characterized by abnormal lymphocytes in the blood, bone marrow, or lymph nodes. These diseases progress slowly, and while most patients require long-term management, treatment remains challenging.

Following a comprehensive assessment, BMS believes that surrogate endpoints could be the key to “breaking the deadlock”—by using complete response (CR) or complete response with incomplete hematologic recovery (CRi) within one year post-treatment as a surrogate endpoint for progression-free survival (PFS), it aims to secure accelerated FDA approval.

However, while the FDA acknowledged BMS’s trial design, it required BMS to provide robust clinical validation and statistical evidence. To meet the FDA’s stringent review criteria for surrogate endpoints, BMS needed not only to demonstrate a clear association between CR/CRi and long-term patient survival but also to validate that the data used constituted valid comparative data.

Medidata’s data repository aggregates historical trial data from over 36,000 clinical trials spanning diverse disease areas and mechanisms of action, involving more than 11 million patients, thereby enabling the conduct of such studies.

Aligned with BMS’s objectives, Medidata aggregated data from more than five historical clinical trials, encompassing over 1,600 patients with relapsed/refractory chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL) who had previously received at least one prior therapy (BTK inhibitor, BCL-2 inhibitor, PI3K inhibitor, or anti-CD20 monoclonal antibody). Additionally, time-to-event analyses were conducted to evaluate the association between achieving and maintaining complete response (CR)/complete response with incomplete hematologic recovery (CRi) at 12 months post-treatment and long-term patient survival.

Based on the aforementioned historical datasets, Medidata built a comparative model for BMS within weeks and provided BMS with the results of comparative analyses of prognostic factors and post-treatment response data to support the scheduling of its clinical trials and regulatory meetings.

Ultimately, Medidata’s comparative data demonstrated that achieving and maintaining complete response (CR) or complete response with incomplete hematologic recovery (CRi) within 12 months post-treatment was significantly associated with improved long-term survival outcomes. These findings indicate that CR/CRi response within 12 months after treatment can serve as an early response endpoint for assessing progression-free survival in the patient population. This provided foundational evidence for Bristol Myers Squibb’s (BMS) application to the U.S. Food and Drug Administration (FDA) for accelerated approval, leading to the FDA’s first approval of a CAR-T therapy for patients with chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL).

The aforementioned trial evidence, along with other data provided by BMS, enabled the drug to complete its market launch in March 2024, several years ahead of schedule.

Overall, by leveraging high-quality historical datasets and AI models, Medidata not only provides insights for clinical trials but also reduces the risk of patient dropout, ensuring that trials are completed smoothly and on schedule while achieving cost reduction and efficiency improvement.

For sponsors, this means that the drugs they have strived to develop could reach the market several years ahead of schedule, with the opportunity to become the first approved therapy for new indications in a breakthrough manner; for patients, this represents an accelerated pathway to new therapies, offering the potential to cure more patients and ultimately providing new possibilities for improving quality of life.

Looking ahead, Medidata stated that it will further leverage its expertise in AI to integrate the development and benchmarking of surrogate endpoints with technologies such as external control arms and digital twins, thereby delivering personalized, patient-level predictions.

Thus, Medidata not only enables sponsors to fully understand the potential of a drug to surpass previous R&D benchmarks and make informed trial decisions on how to accelerate development efficiency, but also provides credible evidence derived from historical data to demonstrate whether a new therapy is superior to standard of care across different treatment scenarios. All of this ultimately serves to demonstrate the R&D value of innovative drugs to regulatory authorities, thereby bringing hope to patients’ lives.

Of course, the development of AI is not an overnight achievement. Medidata will explore the frontiers of digital intelligence in clinical trials, leveraging “intelligence” to enhance “quality.” By drawing on accumulated experience and driving digital-intelligence innovation, Medidata aims to help more high-quality therapies break through barriers, thereby saving and improving the lives and quality of life for more people.