IAG Partners with Better Medicine to Optimize Oncology Imaging Trials

Faster, Cheaper Oncology Imaging Trials: AI-Driven Central Reads with Image Analysis Group and Better Medicine

Image Analysis Group (IAG) and Better Medicine have entered into a strategic partnership to deliver faster, more cost-efficient central reads and advanced AI-powered imaging endpoints for oncology clinical trials. This collaboration is designed for biotech and pharma sponsors seeking a specialist imaging CRO that can streamline oncology imaging workflows, reduce central read turnaround times, and lower overall imaging costs while maintaining regulatory-grade quality.

Oncology Imaging CRO partnership

Under the partnership agreement, IAG integrates Better Medicine’s lesion and tumour-focused AI analytics into its global clinical trial imaging operations, covering multi-centre oncology studies across all phases.

Sponsors can access centralized image management, blinded independent review, and automated tumour measurement workflows that support common oncology response criteria and bespoke exploratory endpoints.​

The partnership focuses on improving time-to-result and consistency in oncology central reads by combining expert radiology oversight with scalable AI-driven pre-processing and quantification. This model is particularly relevant for sponsors running complex imaging protocols in solid tumours who need rapid, reliable imaging endpoints to support dose selection, go/no-go decisions, and submission-ready data packages.​

“We are thrilled to partner with Better Medicine to bring this powerful combination of technologies to our clients,” said Dr. Olga Kubassova, CEO of Image Analysis Group (IAG). “The integration of their advanced AI into our DYNAMIKA platform will provide an even more robust and efficient solution for managing clinical trials. IAG is working with other endpoint partners as well to bring their unique, deep tech to benefit the drug approval process. This partnership underscores our commitment to leveraging innovative technologies to accelerate drug development and bring new therapies to patients faster.”

Faster and more efficient central reads

The collaboration enables IAG to offer streamlined central reading services where AI tools assist with tumour detection, segmentation, and change assessment, reducing manual workload and cycle times. Partners will provide Sponsors with the quality metrics, giving transparency on expected read speed and performance across oncology trials.​

By embedding Better Medicine’s API and platform within IAG’s DYNAMIKA-based workflows, imaging data can move securely from upload to quality control, AI processing, and expert review in a single integrated pipeline. This reduces operational friction, minimizes re-reads, and helps sponsors keep imaging on the critical path for database locks and interim analyses.​

Cost-effective AI-supported Imaging

This partnership is structured to support repeatable, scalable use of Better Medicine’s AI within IAG-led projects, enabling pricing models that reflect automation gains and reduced manual read effort. This framework allows the Partners to invest in improving AI-assisted oncology imaging over time, delivering better value and performance to Sponsors looking to modernize their imaging strategy.​

For Sponsors, this creates opportunities for more cost-effective central reads in oncology trials without compromising on regulatory expectations for audit trails, validation, and reader oversight.​

“This partnership with IAG is a significant milestone for Better Medicine,” said Priit Salumaa, CEO of Better Medicine. “IAG’s DYNAMIKA is a world-class platform for managing imaging in clinical trials, and we are pleased to be able to work together to bring our precise AI driven solutions to a wider audience in the clinical trials space. We are confident that this collaboration will help to accelerate the pace of cancer research and ultimately improve patient outcomes.”

Key benefits for oncology sponsors

For oncology companies searching for an imaging CRO partner, the IAG–Better Medicine collaboration offers:

• Faster central read turnaround through AI-augmented lesion and tumour assessment with and integrated workflows.​
• Lower total imaging costs by reducing manual reading burden and improving first-pass quality.​
• Robust, compliant infrastructure with clear auditability, data security, and validated AI use in clinical trial imaging.​
• Flexible Statements of Work that adapt to phase I–III oncology programs, exploratory biomarkers, and complex multi-country studies.

For more information contact: contact@ia-grp.com or visit: www.ia-grp.com

About Better Medicine

Better Medicine is an Estonian medical AI company developing CE-certified software tools that support earlier, faster, and more accurate cancer detection in radiology. Clinically its BMVision platform integrates into routine CT imaging workflows to automatically detect, measure, and classify oncological findings, beginning with kidney tumours, helping radiologists improve diagnostic efficiency and reduce the risk of missed lesions. Expanding beyond this into clinical trial workflows the company also provides multi-organ AI driven lesion segmentation tools on CT scans to automate repetitive tasks for oncology trials and research. Founded in 2020, Better Medicine collaborates with leading hospitals and research centres across Europe, the UK, and other regions to advance AI-supported cancer diagnostics and patient outcomes.

About Image Analysis Group (IAG)

Image Analysis Group (IAG) is a global imaging clinical research organization (iCRO) specializing in designing and running imaging-centric clinical trials across oncology, immunology, neurology, rare diseases, and musculoskeletal conditions. Through its proprietary cloud-native platform, DYNAMIKA, IAG combines centralized imaging workflows, expert readers, and AI-powered endpoints to deliver high-quality, regulatory-ready imaging data that accelerates drug development and reduces trial risk. IAG partners with biotech and pharma sponsors worldwide to optimize imaging strategies from early proof-of-concept through pivotal and real-world evidence studies.​