THE MEDIDATA EXPERIENCES

단순한 전략 그 이상.
실행 가능한 유일한 운영 모델.

임상시험은 이제 구조적 한계에 도달했습니다. 프로토콜은 더욱 복잡해졌고, 데이터의 양은 폭발적으로 증가했습니다. 하지만 여전히 많은 조직들은 서로 단절된 시스템을 사용하며, 이를 조정하는 인력에 의존해 운영을 이어가고 있습니다.

환자(Patient), 데이터(Data), 그리고 스터디(Study)를 아우르는 연결된 경험이 오늘날 대규모 임상 연구를 지속할 수 있는 유일한 운영 모델입니다.

Video transcript: The life sciences industry is shifting towards holistic solutions to not just extend lives, but improve them. Modern trials demand doing more with less. You need a trusted partner that solves complexities while achieving better, faster outcomes through technology, AI, and expertise. That's why we designed the metadata experiences. These patient, data, and study experiences unite for peak speed, efficiency and decisive action. So you can unleash clinical data's might, ignite insights and forge lasting trust and participation in your trials. All this powered by Metadata's unified platform with AI driven intelligence informed by over thirty six thousand studies. Don't just run trials, revolutionize them. The future of clinical research is here and it's built on experience. Are you in?

하나의 운영 시스템(OS)으로서의 경험

의뢰사와 CRO는 더 이상 단순한 개별 솔루션을 원하지 않습니다.
그들은 엔드 투 엔드(End-to-end) 워크플로우, 벤더 복잡성 감소, 통합 포인트 최소화,
그리고 수치로 증명되는 가속화를 요구하고 있습니다.

연결된 경험은 데이터와 워크플로우, 실시간으로 서로 정보를 주고받으며 의사결정을
보완하는 ‘지능형 통합 시스템’을 구축함으로써 임상시험 전체를 강화합니다.

검증된 글로벌 플랫폼

80 %

2025년 FDA 신약 승인

전 세계의 신뢰

2.3 K+

140개국 이상의
고객 및 시험기관

내장된 AI 기술

70 B+

연간 데이터 포인트

수십 년간의
종단 데이터

38 K+

임상시험에
메디데이터 기술 적용

Patient Experience

임상시험 ROI를 높이는 참여

임상시험 전 기간은 물론 그 이후까지도, 더 강력한 참여자 모집과 신속한 등록, 적극적인 참여, 향상된 복약 순응도, 그리고 지속적인 유지를 실현할 수 있습니다. 

임상시험의 부담을 줄이고 워크플로우를 간소화하는 통합 플랫폼을 통해, 환자와 임상시험 기관 모두에게 강력한 실행력을 제공합니다.

Patient Experience 살펴보기

Data Experience

학습하는 데이터. 행동하는 AI.

임상시험 전 과정에 걸쳐 데이터는 비약적으로 증가합니다. 언제 어디서나 데이터의 무결성(Integrity), 가시성(Visibility), 인사이트를 확보할 수 있도록 데이터를 체계적으로 설계하고, 관리하며, 그 가치를 극대화할 수 있습니다.

스터디 빌드부터 데이터베이스 잠금 단계까지, 지능형 자동화를 통해 데이터 워크플로우를 간소화하고 데이터 품질을 혁신적으로 개선합니다.

Data Experience 살펴보기

Study Experience

결과 예측. 성과 가속화.

임상 설계 단계에서 실행 단계로 전환하는 전 과정에서 완벽한 가시성을 확보할 수 있습니다.

내장된 AI와 예측 분석 기술을 활용하여, 임상 계획 수립과 실행을 가속화합니다. 위험 요소를 미리 예측하고 조기에 대응함으로써 성공적인 임상 운영을 실현합니다.

Study Experience 살펴보기

Featured Resource


코드 그 이상: 임상시험 경험의 혁신

BBC StoryWorks가 제작한 시리즈에서 Medidata 리더들을 통해 AI와 머신러닝이 어떻게 임상시험을 혁신하고 있는지 살펴봅니다.

Video transcript: I always knew I wanna be an astronaut when I was growing up. So these are just some of the kids' models that I've had for I don't even know how many years. And you've got space shuttle. This is everybody's dream. I got into college and really started pursuing my dream of becoming an astronaut. But unfortunately, in my sophomore year, got very sick and was diagnosed with Hodgkin's lymphoma. It took me a while to really wrap my mind around how significant my life was about to change. You know, when I got to college, I was so focused. I wanted to be an aerospace engineer. I wanted to go to space. Cancer really took that away from me. I just going through what I had to go through took a toll. So after graduation, I actually started my career in information systems. Ten years, into my career, I was diagnosed with breast cancer. It was a direct result of all the radiation I had is for my treatment with Hodgkin's disease. I was stunned to see that there had really been no change in the patient experience from when I was first diagnosed in nineteen ninety with Hodgkin's lymphoma and decided to step into helping health care improve the patient experience. The patient experience is critical in thinking about how you design studies and how clinical trials are ultimately executed. Clinical trial participation can be very tough on patients. It's incumbent upon all of us to put a focus on patients and the value that they bring to the research community and to take care of them as best as we can in the context of these studies. Our focus here is to lower the bar of participation by making it easier for them to capture data from home and minimizing the amount of time and effort it takes them to be able to participate in a study. So myMedidata is an app that patients use at home to provide their own information on how they're doing on the clinical trial. It helps reduce burden because patients give us the information that they have at home on a daily basis instead of waiting until they visit their doctor. And it also helps improve the fidelity of the data we get because we're getting it in real time. Yeah. And that and the the data life for a patient doesn't just start when the clinical trial starts. Oh, gosh. You've got all sorts of data before. When you take time to incorporate the patient perspective in clinical trial design, you pick up the nuance. You understand better how a patient's gonna move through that clinical trial experience. We've amassed a really valuable data set. Our view of the future of clinical research is that we find better ways to harness these data very quickly and then to layer on the power of AI so that we can accelerate the process of finding new therapies as fast as possible. So for this single simulant, the data are abstracted from potentially multiple patients. So simulants is part of our AI program. And the whole idea behind simulants is that we take this very large dataset that we have of of historical clinical trials data and we mix and match the information from lots of different patients to create simulated new patients that are actually AI constructs, but which are so close to the actual real patient that we can use those simulations as part of the research effort moving forward. AI. In some cases, we're able today to replace entire arms of clinical research studies, and we call this program synthetic control arms. Because we can take a patient who otherwise would have been brought onto a trial just to receive a standard of care or a placebo dose, and we can replace that patient with a synthetic control patient so that the real person doesn't have to be exposed to the placebo. We have highly sophisticated data, so privacy protection and abstracting away from the identifying information and those data are absolutely critical to what we do in our AI program. The clinical trial process is evolving at an enormous rate. There's an explosion of data availability being created in the world, and our long term goal as a company is to build full, what we call virtual twin models, where a person can have a perfect data twin. We bring a huge benefit to patients because the more we can use their virtual twin or programs like simulants, the more we can replace the kind of exposure that patients ultimately have to have on the trial. The reality is people are always gonna be dealing with illness or disease, but we're using the technology that's available to us today to make that experience better for the people that are dealing with these illnesses. I've accepted that I'm never going to the moon, but I have to say back here on Earth, I like to think that what we're doing at Medidata is really out of this world.
Video thumbnail

FAQ

Medidata Experiences는 단일 지능형 플랫폼에서 환자(Patient), 데이터(Data), 연구(Study) 워크플로우를 통합합니다. 이를 통해 임상시험 전 과정에 걸쳐 사람과 프로세스, 그리고 시스템을 하나로 연결합니다.

AI는 모든 워크플로우에 내장되어 리스크를 감지하고, 데이터 품질을 개선하며, 반복적인 업무를 자동화합니다. 또한, 즉각적인 대응이 가능한 실시간 인사이트를 통해 의사결정을 지원합니다.

의뢰사와 CRO는 더 이상 단순한 개별 솔루션을 원하지 않습니다. 그들은 엔드투엔드(end-to-end) 워크플로우, 벤더 복잡성 감소, 통합 포인트 최소화, 그리고 수치로 증명되는 가속화를 요구하고 있습니다.

경험(Experiences)을 연결하는 것은 단순히 소프트웨어를 도입하는 차원을 넘어, 운영의 근본적인 혁신을 의미합니다. 규모의 경제, 데이터의 깊이, 규제 전문성, 그리고 내장된 지능형 기술이 결합된 독보적인 파트너와 함께하십시오.

상담하기

질문이 있으신가요? 가격 정보 또는 다음 단계에 대해 알아보고 싶으신가요? 지금 전문가와 상담하세요. 저희 팀이 도와드리겠습니다.

문의하기