Current industry trends align with the need for improved, fit for purpose technology.
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Contract research organizations (CROs), biotech companies, and pharmaceutical firms face significant challenges when designing, planning, and executing clinical trials.1 These obstacles include high costs, resource inefficiencies, lost time, limited risk visibility, outdated processes, operational complexity, regulatory hurdles, talent shortages, and the ongoing struggle to adopt digitalization and automation solutions.2 These challenges are not isolated but global, impacting organizations across the board and resulting in widespread inefficiencies.
Clinical trials are notoriously expensive, with operational expenses ranging from $50 million to over $115 million.1 The median cost of a clinical trial phase is approximately $19 million,3 a figure that represents a fraction of the total cost of developing a new drug—estimated at $2 to $3 billion USD.3 The median cost per patient in a pivotal trial is around $42,000.4 Rising costs place a heavy burden on healthcare systems, reducing patient access and stalling innovation, particularly for rare diseases and orphan drugs that lack cost-effective strategies and payer subsidies.5
Beyond direct costs, CROs incur significant expenses in the pre-award phase, creating strategic proposals to compete for trial contracts from sponsors. These activities, often unpaid, cost millions annually and may not result in awards, adding to the financial strain. The traditional reliance on fragmented tools, platforms, and data sources exacerbates inefficiencies, leading to poor risk visibility, extended timelines, and inconsistent operations.
Feedback from the Aurora Analytica Insights Survey (2024)6 underscores the industry’s dissatisfaction with the status quo:
Biotech companies often lack the resources to conduct trials in-house, relying on CROs for operational expertise. Even large pharmaceutical firms frequently outsource to CROs to leverage their experience across therapeutic areas. However, this reliance can breed distrust as CROs occasionally overpromise and underdeliver, causing delays and cost overruns—further hindering timely patient access to new treatments.
By addressing inefficiencies and adopting streamlined, data-driven approaches, clinical technology providers can drive meaningful change. Lowering costs, reducing risks, and ensuring quality and reliability empower sponsors to allocate resources more effectively, enabling greater focus on neglected areas, such as rare diseases.
For clinical trial specialists—feasibility experts, data scientists, medics, project managers, commercial and operational leads—the current process of synthesizing and leveraging data across platforms is slow, error-prone, and inefficient. Disconnected systems cause delays, hinder critical insights, and obstruct trial progress. Key areas like country selection, site identification, and patient enrollment are significantly impacted, creating bottlenecks that delay life-saving treatments and limit revenue opportunities.
The feedback from industry surveys aligns with the challenges identified by Aurora Analytica. There is an urgent need for a unified, efficient, and data-integrated platform to address fragmented trial management. Novel AI-powered platforms can bridge the gap between disparate systems, fostering collaboration, reducing inefficiencies, and empowering clinical trial teams to achieve better outcomes.
By enabling faster, more reliable decision-making, key technology providers develop fit for purpose tools necessary to improve trial efficiency, accelerate timelines, and ultimately deliver life-saving treatments to patients in need.
Bhavish Lekh, CEO & founder at Aurora Analytica