ZS Launches ZAIDYN Clinical Development, Expanding Its Digital Life Sciences Platform

ZAIDYN Clinical Development empowers life sciences companies to break down silos in clinical trial design and planning, remove barriers to enrollment and engagement, and bring better products to patients faster.

Global management consulting and technology firm ZS has announced the launch of ZAIDYN Clinical Development. The offering is the latest expansion of the platform ZAIDYN by ZS, designed to empower life sciences companies to digitally transform and scale customer engagement, field performance, analytics and—now—clinical development design and planning.

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“ZAIDYN Clinical Development will help our clients navigate the large-scale, disruptive changes we see happening across our industry—and those on the horizon as AI and machine learning transform clinical research and development (R&D)”

“Today, we’re announcing the launch of ZAIDYN Clinical Development, expanding on more than 35 years of software expertise,” said Sanjay Joshi, managing principal and platform lead for ZS. “With ZAIDYN, life sciences organizations can connect their global teams, products, processes, applications, algorithms and data assets for powerful insights to shape clinical research and accelerate clinical development timelines. Our platform works with existing IT systems to fuel efficiency and connectivity, reduce costs and empower life sciences companies of all sizes to innovate, scale and grow as the global healthcare ecosystem evolves.”

ZAIDYN Clinical Development harnesses the power of a self-learning network, AI-driven insights and algorithms to create a fluid, fast, frictionless trial experience for business users, site investigators and patients. With our products, companies have the power to:

• Drive innovation and decision-making throughout the clinical development process with insightful, dynamic reporting and analytics for clinical teams and a high-level view of clinical trial operations for leaders
• Optimize clinical study planning and protocol design using AI and predictive insights that reflect the experiences and perspectives of participants and patients
• Empower teams to test and model site and enrollment scenarios to find ways to make studies more inclusive and engaging, lift participant burden, limit amendments and accelerate trial efficiency
• Create an expanding universe of industry and historical clinical trial data, real-world data, site criteria and patient survey insights
• Raise the bar for clinical research with products built on Amazon Web Services (AWS) that apply the latest clinical data standards and fuel connectivity throughout upstream and downstream systems

More than 130 companies already use ZS’s products to drive business decisions. Now, these companies can combine the clinical expertise of ZS consulting with the latest features of ZAIDYN Clinical Development to break down business and clinical silos and empower teams to work together more efficiently.

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“ZAIDYN Clinical Development will help our clients navigate the large-scale, disruptive changes we see happening across our industry—and those on the horizon as AI and machine learning transform clinical research and development (R&D),” said Aaron Mitchell, ZS’s global R&D excellence practice leader. “Smarter platforms for life sciences can help us improve clinical trial diversity, bring life-saving therapies to patients faster, and unlock patterns and breakthroughs that will transform the future of clinical research. It’s all about using insights from data more effectively to drive more inclusive studies and better patient outcomes.”

“With the support of ZS and the ZAIDYN platform, we’re accelerating the transformation we initiated three years ago,” reflected Cynthia Deparis, program manager at Sanofi. “The platform is helping us take a data-driven approach to identifying the best countries and sites for clinical studies. It’s helped us integrate and expand the universe of clinical operational trial data so we can target sites and countries that help us deliver on our development portfolio and think through various strategic parameters like the competitive landscape, our peers’ activity, historical knowledge about sites and feedback from outreached sites. With these insights and the ability to model different scenarios, we can continue to optimize recruitment and enhance the accuracy of our projections, setting our clinical trial development on a continuous improvement cycle.”

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