Cytel Inc.

How should the use of gen AI be transparently and consistently reported within HEOR workflows? The solution: the reporting guideline ELEVATE-GenAI. Here we offer an overview of this guideline: hubs.ly/Q047Gb5V0

Analyzing endpoints in multiple sclerosis clinical trials can present several statistical challenges. We define common endpoints in MS trials and discuss the key statistical modeling techniques to analyze them. hubs.ly/Q047Gh7d0

Central Statistical Monitoring (CSM) proactively detects emerging risks to data quality, safety, and trial conduct. Join us for our upcoming webinar on how CSM can streamline oversight, reduce SDV, and deliver cost savings in site monitoring. hubs.ly/Q047h0Lr0

EMA/FDA “Guiding Principles of Good AI Practice in Drug Development” provides, for HEOR, something the field has long needed: a regulatory blueprint for responsible AI use that could help agencies move from cautious experimentation to structured adoption. hubs.ly/Q046W16Y0

At ACDM26, Jenn Sustin will discuss how CDEs are pivotal in modern clinical research, serving as the architects of data infrastructure that transforms raw, heterogeneous clinical data into structured, analysis-ready assets. hubs.ly/Q046JgD50 We hope to see you in Berlin!

Clinical trials grow more complex & the traditional model of on-site monitoring is no longer sufficient. Reg. expectations have evolved, trial budgets are under pressure & sponsors need earlier, more objective insights into risks. CSM meets these demands: hubs.ly/Q046tplz0

CDISC IG 4.0 and SDTM 3.0 have just been released for public review, with comments due April 6. Angelo Tinazzi discusses the main changes expected with these updates, including structure of new datasets, three new proposed domains, and changes to metadata.hubs.ly/Q04631w_0

Many new Alzheimer’s drugs reduce amyloid beta (Aβ) levels, and some have even been approved based on this effect. But does lowering Aβ actually translate into meaningful clinical benefit? Dalia Dawoud shares her research on Aβ as a surrogate marker. hubs.ly/Q045-m0-0

Today’s trials generate unprecedented volumes of complex data, introducing challenges that require new approaches. We discuss the expanding complexity of clinical data & the specialized roles needed to bridge clinical knowledge, data science & technology. bit.ly/4cZmUUg

In many development programs, traditional RCTs are not feasible or may raise ethical concerns. ECAs leveraging RWD are emerging as the pragmatic approach: bit.ly/4sptWX7

AI systems are becoming increasingly embedded across clinical development workflows, and transparency is essential. The 2025 FMTI evaluates how openly AI model developers disclose information about data, compute, evaluation methods, and governance: bit.ly/4chmpER

The FDA has just announced that its new standard for approval will be one pivotal trial, ending a decades long “two trial dogma.” Jürgen Hummel discusses this landmark policy change, the focus on trial design and analysis, as well as remaining questions. hubs.ly/Q044Mqm60

At ACDM26, Jenn Sustin will discuss how CDEs are pivotal in modern clinical research, serving as the architects of data infrastructure that transforms raw, heterogeneous clinical data into structured, analysis-ready assets. hubs.ly/Q044zNtd0 We hope to see you in Berlin!

The FDA recently released its Draft Guidance on the use of Bayesian methodology in clinical trials — what do sponsors need to know? Join us for an interactive office hours session to gain clarity on FDA expectations regarding applying Bayesian methods: hubs.ly/Q044zPrP0

GenAI is rapidly reshaping the landscape of clinical documentation and holds enormous promise for the future of pharmacovigilance. We discuss how GenAI can improve the speed and consistency of writing PSNs, while maintaining compliance with ICH standards. hubs.ly/Q044q1qN0

AI in HEOR is here to stay, but there is often a gulf between understanding AI regulations and effectively implementing GenAI responsibly. Join us for an insightful webinar exploring regulatory & HTA perspectives from EMA, FDA & NICE, and two use cases. hubs.ly/Q0444qL90

The FDA recently released its Draft Guidance on the use of Bayesian methodology in clinical trials — what do sponsors need to know? Join us for an interactive office hours session to gain clarity on FDA expectations regarding applying Bayesian methods: hubs.ly/Q043xf9q0

The EMA/FDA have published the “Guiding Principles of Good AI Practice in Drug Development.” For HEOR, this provides a credible regulatory blueprint for responsible AI use that could help agencies move from cautious experimentation to structured adoption: hubs.ly/Q043xmTT0

CDISC IG 4.0 and SDTM 3.0 have just been released for public review, with comments due April 6. Angelo Tinazzi discusses the main changes expected with these updates, including structure of new datasets, three new proposed domains, and changes to metadata.hubs.ly/Q043jlFP0

Modern trials increasingly rely on data from EHRs, wearable devices, mobile apps, genomics, imaging, and RWE. These complex datasets have necessitated two new roles: Clinical Data Scientists and Clinical Data Engineers. Register today for the webinar: hubs.ly/Q0437ZBz0