The U.S. Food and Drug Administration (FDA) and the European Medicines Agency (EMA) have rigorous processes for reviewing applications for new drugs for marketing. By working with an experienced partner who can focus on the approval process from preclinical studies up to pivotal clinical investigations for you, the development is more likely to proceed along targeted timelines as you concentrate on the actual science.
If your novel oncology asset application has raised concerns during approval, you may be called to an advisory meeting. It’s a best practice to anticipate issues beforehand. CATO SMS calls this “pre-anticipation.” By identifying any potential weak spots that may result in either refusal or long delays, you can set up your application for a greater chance of success.
Keep in mind what the FDA’s Oncological Drugs Advisory Committee (ODAC) and the EMA/CHMP’s Scientific Advisory Group of Oncology (SAG-O) primarily want to know — is the risk-benefit profile of the drug sufficient for the intended use in cancer patients?
To best qualify for this term, you should keep in mind these four critical areas that we identified as causing most comments during reviews:
- Dose selection
- Statistical analysis plan (SAP)
- Quality of life (QoL) and patient reported outcomes (PROs)
- Eligibility criteria and patient selection
In our blog, we will explore pre-anticipation of your oncology asset and dossier in these four areas. If you are looking for a deeper dive into the complete pre-anticipation process, you can find more detailed information in our recent webinar. In there, you can find highlights and details on what is most often overlooked — and what will have significant consequences if not addressed and mitigated early.
Pre-anticipation is an essential process to the product’s success. Navigating it correctly will help you be prepared for and excel at the regulatory authorities’ reviews. Here is what you need to pay special attention to:
Getting the Doses Right
A dose/dosing schedule should be determined early in the development process. Understanding the mechanism of action and the pharmacokinetics of the new product will assist with the identification of the optimum dose. Also, in the early phases of development, analytical assays may not be in place to reliably evaluate a dose response. Current drugs no longer follow the “more is better” principle but need to be considered specifically based on their anticipated mode of action. To identify the no-effect, minimum-effect, and maximum-effect safe doses, researchers can evaluate the dose-dependency and dosing schedule to find the limiting toxicities in nonclinical studies and then estimate the safe and comparable dose in humans. It is also helpful if efficacy and toxicity can be explored in the same species. The minimum effective dose can be found with the appropriate study design. Finding the minimum effective dose is essential, and you must clearly convey your dosing rationale with supportive nonclinical data to ensure approval or minimize approval delays.
Sanctity of the Statistical Analysis Plan
The statistical analysis plan (SAP), which includes details and instructions on how to analyze clinical study data, requires careful preplanning. It ensures the integrity of clinical data, and it predefines the data analysis according to study objectives.
Because of its importance, multiple stakeholders must give input to your SAP throughout the study, especially in oncology and during this era of “big data.” Complex genomics and proteomics data need to be integrated into the study analytics.
Changes to the SAP during the study must be documented in the clinical study report (CSR), highlighting the impact on study results. If the SAP is changed after data analysis, results may seem biased.
The CheckMate-227 study offers a good example of problematic SAP changes. Upon review, the study had extensive changes in subgroups and their analysis. Biomarker- and treatment-group adjustments in different cohorts were pooled across multiple database locks (DBLs). The EMA had concerns about the data handling and inconsistencies, and reliable conclusions were not possible.
To avoid bias, adequate procedures in the following areas need to be set:
- Handling of data reviews before DBL
- Defining the study population
- Handling of missing data, outliers, and protocol deviations
- Defining subgroups in the analysis
Importance of Quality of Life and Patient Reported Outcomes Data
Drug approvals are indisputably based on safety and efficacy measurements, but quality of life (QoL) and patient reported outcome (PRO) measurements are also crucial. Your study design should be patient-centered and enable patient community engagement.
QoL and PRO instruments should be chosen based on validity, sensitivity, and reliability. If there are no statistical or only limited clinical differences between a new drug and standard of care treatment, reviewers may look at the patient reported data more closely. QoL or PRO instruments need to be further considered specifically in oncology studies in terms of missing data, timing of the assessments, and requirements for training of the research staff.
Patient Enrollment in Clinical Studies
The advisory committee will be interested in the inclusivity of your study’s eligibility criteria and the rationale for any exclusions. In addition, you will need to determine, based on your study design, if the eligible patient population in your study is representative of the patients likely to receive your drug, if approved.
According to Marc B. Garnick, Gorman Brothers Clinical Professor of Medicine at Harvard Medical School and physician at Beth Israel Deaconess Medical Center, exclusion criteria are often too restrictive in oncology studies. In his experience, it is common to find that drug safety has not been determined in the population that the drug is intended for.
Overly restrictive eligibility criteria also slow study accrual, jeopardizing generalizability of results, and limit the clear understanding of the risk-benefits of the product. To avoid eligibility questions, any rationale for excluding patients should reflect the expected toxicities associated with a new therapy.
In summary, at the onset of your oncology drug development program, ask these pre-anticipation questions:
- Can you correctly determine the dose and schedule based on the nonclinical results?
- Is the SAP predefined and if changed then transparently documented? What is the effect of the changes to the study integrity?
- Are QoL/PRO instruments available that could be reported to support the dossier? Which patient population will ultimately benefit from the new drug and is that population sufficiently represented in the eligible population?
A pre-anticipation checklist and review will save time in the long run, and you will be able to avoid obstacles that could delay your product from reaching the market. Working with a knowledgeable partner who understands how to navigate these nuances provides a key advantage.
For a more in-depth discussion around anticipating obstacles to approval, watch our webinar, Pre-Anticipation: Anticipating Obstacles to Approval Before Phase I in Oncology Drug Development.