Personalized Medicine Can Lead To Optimized Clinical Trial Design, Improved Selection of Therapeutic Candidates
Jeff Elton explains how the need for more targeted, personalized therapies, are requiring changes throughout the drug development process, and how best your company can adapt.
When developing new medicines, pharmaceutical companies must place a focus on total product value, health, and quality of life outcomes. By doing so, pharmaceutical companies can best determine which medicines to develop and commercialize -- those which are not only efficacious, but also which deliver value to health care systems as well.
The increasing emphasis on total therapeutic product value and personalized medicine is requiring pharmaceutical companies to make changes in their clinical development and management processes
The increasing emphasis on total therapeutic product value and personalized medicine is requiring pharmaceutical companies to make changes in their clinical development and management processes, including optimizing their clinical trial designs to more effectively identify medicines that offer value.
The biggest inadequacy of current clinical trial designs involves the poor selection of proper drug targets. Many of these candidates fail in the later stages of clinical trials -- during Phase III. It is our belief that clinical trials must be redesigned so that scientists and clinicians know whether a candidate therapeutic is efficacious and provides benefit and value early on in the first few patients rather than later, saving time, money and other valuable resources. If a candidate therapy fails, we can harness the tools of personalized medicine, such aspharmacogenomics, to assess the molecular makeup of individual patients, and determine whether failure of a therapeutic was caused by the makeup of an individual patient's genome.
Partners in Trial Designs
We see that early phase collaborations can aid in improving clinical trial designs. Diagnostics companies or groups should work with the therapeutics team to identify clinical practical biomarkers or tests. In addition, payer and provider analytics groups can build a perspective on ‘value’ that can be integrated into the design of both early and late phase trials to support a practical assessment of value to patients and the system versus alternative treatment approaches. Practically assessing value creates new pressures to assure that the diagnostic or other patient stratification approaches can be practically deployed in the clinical contexts where the new medicines will be used, such as in community non-acute settings versus sophisticated academic medical centers.
With genomic sequencing, treatments can be tailored to the genetic anomalies of an individual's tumor, which may be quite different from those of another patient’s tumor
Pharmaceutical companies, diagnostic companies, and academic or government-based research centers can become partners in designing new clinical trials, sharing their knowledge and expertise. For instance, Novartis is using Foundation Medicine's genome interpretation technology as part of its clinical trial enrollment process for cancer drug testing[i]. This tumor genome analysis technique involves seeking potential drug targets in the genetic sequence of tumors. With genomic sequencing, treatments can be tailored to the genetic anomalies of an individual's tumor, which may be quite different from those of another patient’s tumor.
Incorporate Real-World Data
As part of ongoing efforts to optimize clinical trials, improve personalized medicine, and bring the greatest therapeutic value for patients, pharmaceutical companies should look to incorporate new real-world data, which Accenture defines as data acquired from electronic medical records (EMRs), laboratory information systems, etc. Real-world data is collected in the actual clinical care environments where patients are treated. It is different than data collected from controlled environments, such as controlled clinical trials. Real-world data offers valuable insight into the effectiveness of different medicines. It facilitates coverage and reimbursement decisions.
Gaining access to EMR derived real-world clinical data helps pharmaceutical manufacturers better personalize therapeutics and stratify populations, optimizing value and patient outcomes. Using EMR derived real-world data could help pharmaceutical companies and health care providers identify specific opportunities within populations of patients, look for collaborative approaches, and measure the benefits from their unified approach.
We find that increasingly, clinical trial designs must:
- Anticipate that EMR data will be collected on an ongoing basis, showing for whom the medicine works, and for whom it is less effective;
- Include approaches that incorporate the medicine in a real clinical context;
- Build the foundation for value.
EMR data can provide noteworthy evidence on the efficacy, benefits and possible negative effects of new personalized medicine treatment options under consideration, showing how value is being realized from their therapeutics and associated treatment approaches.
EMR-derived real-word data and associated analytics can come from several sources:
- Academic centers that provide rich insights into specific disease states and targeted patient populations;
- A growing number of health payer enterprises that collect and analyze claims-derived information;
- Third party firms aggregating EMR derived data across multiple health delivery systems.
In each of these cases, payers, third-party aggregators, and the leading academic medical centers are providing a consistent data model and analytic tools that make possible insights into the use and value of current medicines, which, in turn, can guide the design and endpoints for a new personalized medicine's value plan.
The Integration of Approaches to Optimize Trial Design
As many of the new therapies under development today are personalized, or targeted, clinical trials also should be more thoroughly personalized, or targeted. Essentially, clinical trials must be designed so that they can show, early on, if a therapeutic is efficacious for the first patients. In a new clinical trial design model, those people taking part in a trial should be selected based on their genetic composition in order to determine their potential for rejecting a therapeutic.
There are several tools that could facilitate this type of genetic analysis, including the use of pharmacogenomics to assess the effects of genetic variation on drug response in individual patients. Another tool might involve using DNA sequencing on all potential participants in a trial to determine which patients would best benefit from a therapeutic, and should participate in the clinical trial.
We suggest that the trial designs and practical therapeutic approaches of the future will increasingly bring together a variety of tools and technologies– next generation sequencing for clinical diagnosis, other diagnostic modalities, real-world evidence from patient populations over time. It is the integration of these approaches that will drive value and enable clinicians and clinical care institutions to realize value consistent with their clinical trials designs and beyond what they are realizing with their current approaches.
What is novel is how these approaches are partnered, who is engaged early on and throughout the process, and who is provided access to the data. It is in the partnering across the development and early commercial life cycle that will engage critical parties, lower risk, and accelerate needed new innovations.
In this manner, pharmaceutical companies can best determine which personalized medicines to develop and commercialize -- those that deliver value to patients and health care systems.
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