While drug failures and successes can be difficult to predict, there are tools available to help drug developers contain clinical development costs and reduce risk. Leveraging technology and optimization techniques, along with the FDA’s advice and experience, can help improve the clinical development process. Dr. Sy Pretorius of PAREXEL discuses clinical trial optimization strategies and how comprehensive data collection has become essential to making informed decisions. –KB
 
Contract Pharma: How can pharma/biopharma companies accelerate clinical development timelines?
 
Sy Pretorius: Challenges in clinical trials can translate into lost revenue and significant delays in getting new, cutting edge medicines to patients. To help clients overcome these challenges, we apply technology services and systems to the clinical development process.
 
Through our Clinical Development Optimization process, we work with companies through the four critical stages of clinical development – design, start-up, trial execution and data submission. The result is data we can leverage to improve protocol design, patient recruitment, site selection and feasibility, and analysis and reporting for our clients, for example:

Design: Protocol design optimization using simulations enables sponsors to identify and quantify the impact of trade-off decisions on program performance, timelines and cost
 
Start-up: Site start-up and clinical trial management systems provide efficient distribution and collaborative compilation of site-level regulatory documents and contracts
 
Execution: Intelligent technology helps predict and capture core operational and scientific data
 
Data Submission: Data aggregation aligned with commercial decision-making strategy can help ensure the right technology and operational support for an initial regulatory application, identification of future opportunities, and product lifecycle management
 
By optimizing these stages, companies can reduce risk, increase clinical trial efficiency, and speed time to market for products and, ultimately, treatments for patients.
 
CP: Where can drug developers look to contain costs?
 
SP: Patient recruitment and protocol-related delays are two significant and costly clinical trial challenges. According to Tufts, 48% of sites miss enrollment targets, and study timelines are often extended to almost double their original length to meet enrollment levels.[1] Additionally, on average, two to three protocol amendments can delay a trial by two months, with each amendment adding $500,000 in additional costs.[2]
 
In addition to lost revenue, challenges in clinical trials can translate into significant delays in getting new medicines to patients. To overcome these challenges, companies can apply advanced technology services and systems to the clinical development process. This in turn gives them access to data for improving protocol design, patient recruitment, site selection and feasibility, as well as analysis and reporting.
 
CP: How can pharma/biopharma companies reduce the risk of late-phase failure?
 
SP: There is no simple solution for preventing late-stage efficacy, safety, or commercial failures; however there are a number of factors that should be avoided early on in the product conceptualization process to help mitigate risk. These include:
 
Applying more rigor to the overall development process – Applying more rigor and discipline to the development process holds potential for weeding out likely failures earlier in the process, thereby reducing Phase III failure rates. For example, avoiding “shortcuts” such as truncated Phase I or Phase II studies in the interest of a “rush to Phase III” and the market, or not listening diligently and thoughtfully to the inputs of regulators prior to launching Phase III.
 
Adequate Phase II Testing – Many Phase III trials fail because of a fundamental lack of understanding of the mechanisms of action of NMEs. Rushing to get to Phase III without adequate understanding of critical components is risky and more often leads to unpleasant surprises in Phase III. Not only does this proposed approach in Phase II make intuitive sense, but it also holds potential for reducing late stage failures.
 
Optimizing Phase III study design with strategies such as:

• More disciplined protocol review and optimization
• Modeling and Simulation
• Adaptive Designs
• Use of Biomarkers

De-risking Phase III Execution – To mitigate study execution risks, pharma companies and CROs leverage data from a variety of sources and conduct ongoing surveillance of the quality of data being collected, while tying this to a properly planned risk-based monitoring protocol.
 
Ensure completeness and clarity of submissions for regulatory agencies – Pharma companies should seek advice from regulators during the drug development process. The FDA offers sponsors and applicants the opportunity to schedule formal meetings at critical points in the development and regulatory process to discuss the plan, and identify areas of concern that may need adjustment. Regulatory Agencies see a vast number of development programs that succeed and fail; their experience can bring significant benefit to sponsors who listen and learn from it.
 
CP: Why is comprehensive data collection so essential to making informed decisions?
 
SP: There is currently a market need for real-time standardization of data in order to analyze information across studies, identify trends, and make critical data-driven decisions in a timely manner.
 
By optimizing protocol design with intelligent trial simulations and scenarios, sponsors can identify and quantify the impact of trade-off decisions on program performance, timelines, and cost. Advanced technology helps identify ‘the signal from the noise’ when assessing patient experience and predictive country/site analytics, providing data-reinforced decisions within feasibility. Ultimately, this allows sponsors to focus on data-driven insights to yield consensus on acceptable risk. From patient recruitment and retention to investigator payments, an optimized process that uses intelligent technology helps predict, capture, and reconcile core clinical data.
 
[1] Tufts Center for the Study of Drug Development Impact Report, January/February 2013.
[2] Tufts International Journal of Environmental Research and Public Health, May 12, 2014.
 
 
Dr. Sy Pretorius is chief scientific officer at PAREXEL and is responsible for leading and enhancing clinical trial innovation. Prior to this role, Dr. Pretorius was responsible for the overall leadership and management of PAREXEL’s Early Phase business unit. Dr. Pretorius started his career as a general practitioner, and subsequently pursued emergency medicine prior to joining the drug development industry. In addition to experience as a Sub- Investigator and later a Principal Investigator, Dr. Pretorius gained relevant exposure in project management, as well as a number of operational, strategic and leadership roles in the PAREXEL offices in Los Angeles, Baltimore, London and South Africa.
 

---

Kristin Brooks has been Associate Editor at Contract Pharma since 2004.