Once your life sciences product has cleared Phase 2 clinical trials, there’s plenty to be excited about—and still a long way to go before you can get to market.
Phase 3 clinical trials tend to be more time-consuming than the first two phases of the Food and Drug Administration’s (FDA) approval process—requiring more patients, more facility space and more funding.
At this stage, more than half of experimental therapies fail due to inadequate efficacy or safety. While this variable can’t really be controlled so late in the development process, you can, however, take steps to prevent the next most common reason for failure: running out of money.
Lack of funding causes more than 20% of therapies to fail in Phase 3. However, equipped with healthcare commercial intelligence, you can make smarter, more confident decisions that improve efficiencies and cost savings in the final stage of development.
Optimize your trial design
A clinical trial is only as efficient as you design it to be, so start with a solid blueprint minimizes costs and leaves room for adjustment as conditions evolve.
Adaptive trial designs allow modifications to the trial after it begins without impacting its validity or integrity. Planning for adaptivity from the start will save you time and money if it becomes apparent that your trial isn’t working as-is.
You should aim to use the minimum sample size necessary to achieve significant results—this will potentially reduce costs. You can determine the necessary figure using statistical factors like margins of error and confidence intervals.
Where possible, leverage technologies to streamline data collection, reduce errors, and lower monitoring costs. These might include electronic data capture systems, wearable devices, or remote patient monitoring techniques.
Avoid screen failures in clinical trials
The U.S. Department of Health and Human Services (HHS) estimates that the average per-patient cost for a Phase 3 clinical trial is over $41,000. Screen failures are a primary driver of these expenses—and one that can be mitigated with the right data, analytics and expert insights into your patient pool.
When a potential participant is screened for inclusion in a study but fails to enroll for any reason, they’re considered a screen failure. Ineligibility (whether due to age, gender, medical history or another factor) is the leading cause of screen failures.
You can leverage healthcare commercial intelligence during premarket research to find experts in your treatment area and facilities with a track record for quickly filling participant pools.
The right experts can help you shape your study criteria to maximize patient eligibility and identify clinical trial participants for whom your product will be most effective. With good profile data, you can even find experts who are professionally affiliated with research sites or potential sponsors, offering additional avenues for cost-savings.
Experts in rare disease states or treatment modalities can provide strategic insights into who your ideal patients are, where they’re located, and how to ensure they make it past screening and stay onboard for the duration of the trial.
Find the right test sites from the start
A typical Phase 3 clinical trial could involve 1,000 patients across a couple of hundred test sites. If a site fails to recruit or retain enough participants, you may need to toss out underpowered results, eliminate or restructure certain testing protocols, or expand to new sites.
Each of these outcomes represents more time and money that your team is likely hard-pressed to provide. Luckily, you can use healthcare commercial intelligence to find reputable test sites near your ideal patient cohort.
Claims analytics and profile data can help you identify key opinion leaders (KOLs) with insights into clinical trials and the ideal test sites for your specific treatment area. These test sites should:
- Have a proven record of successful trial performance
- Feature a team of engaged, expert staff
- Implement recruitment practices that match your trial protocols
- Be located near eligible patients—but far enough from other sites to avoid recruitment competition
Permanent sites with a record for enrollment speed and retention are likely to cost more upfront than remote sites with less experience or rotating staff. Still, it’s nearly always less expensive in the long run to pay more for a site that meets recruitment goals than pay less for one that may never produce eligible results due to inadequate participation.
Improve planning and operational efficiency
While your clinical team focuses on the final stage of clinical trials, your sales and marketing teams are developing their go-to-market strategy. They need insights into healthcare providers’ clinical activity and affiliations to strengthen your product’s positioning and generate pre-launch demand.
Healthcare commercial intelligence combines these insights with medical and prescription claims data and contact information to make it easier to identify and connect with the experts who can help shape your market strategy.
When this information is accessible across your organization from a single, real-time source, your sales, marketing and medical affairs teams can save valuable research hours (and dollars), ensuring your product is ready for commercialization as soon as Phase 3 wraps.
Claims analytics, provider reference data and physician profiles can help your organization make the most of Phase 3 and:
- Identify granular HCO/HCP market segment
- Prioritize territory assignments
- Perform competitive analyses
- Map patient journeys across the care continuum
Explore healthcare commercial intelligence today
In our previous blogs in this series, we asked how early is “too early” for life sciences companies to start preparing for commercialization, and explored how you can accelerate development while reducing risk.
Want to see how our healthcare commercial intelligence platform can help you navigate the FDA approval process from pilot study to post-approval safety monitoring? Sign up for a free trial today and get a firsthand look at our robust data, analytics, and expertise for life science organizations.
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