What makes bringing an oncology drug to the healthcare market so difficult? Cancer therapeutics currently have the lowest clinical trial success rates compared to other major disease states.
Our understanding of the physiology of the cancer disease process is constantly expanding, but many factors can affect the success of a cancer clinical trial.
Absence of Scientific Knowledge
We are constantly learning more about cancer. From solid brain tumors to melanoma to hematologic malignancies, cancer can assume a variety of forms. Precision medicine and new research studies have identified numerous biological markers useful for treating cancer.
This combination of technology and knowledge has led to immense development in anti-cancer therapeutics and cancer care year after year. Immunotherapy cancer treatments have seen an explosion in popularity as more and more cancer cell receptor biomarkers are identified.
Unfortunately, despite this upsurge in knowledge, our understanding of cancer and anti-cancer therapeutics is often insufficient in translating to clinical trial success. Cancer is commonly unpredictable, generating abundant pitfalls in clinical trials related to the disease process or investigational therapeutic.
Investigational or experimental anti-cancer drugs inherently have a large unknown factor associated with them as well. Despite new treatment agents transitioning away from traditional chemotherapies and instead to immunological agents, frequent drug toxicities still exist.
Additionally, some clinical trials may incorporate a drug that may have poorly defined pharmacokinetics and pharmacodynamics, further contributing to the risk of toxicity if overdosed or lack of efficacy if underdosed. Small therapeutic windows are common in oncology trials examining anti-cancer agents, so oncologists and researchers must consider careful dosing.
Fortunately, there are many possible solutions to our lack of understanding of cancer and investigational therapies. Better access to resources can dramatically improve our therapeutic, diagnostic, and prognostic savviness. Rapid advancements in the development of ex vivo culture models and patient-derived biospecimen tissue samples have vastly broadened scientific and pharmacologic understanding.
New approaches such as cryo-preservation of tissue samples allow cancer pathology to be studied to a much greater extent, translating to more well-thought-out clinical studies and clinical trial design.
Building off better access to resources, we can also develop better models. Whether utilizing tissue samples or animal models, there are consistently limitations to the data we can derive. Mouse models are the key mammalian model in cancer studies prior to human dosing, but many limitations still exist before extrapolating crucial animal dosing information towards human studies.
For example, solid tumor biopsy from mouse models should show minimum 30 percent tumor shrinkage as a standard response criterion. Studies show humans rarely outperform these models based on tumor size reduction.
Time-Sensitive Nature of Drug Development
Drug development of anti-cancer agents, like other investigational therapeutics, is an extremely time-intensive and expensive process. Unfortunately for many cancer patients, cancer mortality does commonly allow for an extended enrollment period in prolonged clinical trials. Enrolling patients with advanced cancer in poor prognostic standing can make it difficult to research a potentially valuable therapeutic anti-cancer agent in that population.
In addition, the financial burden of developing a new cancer drug cannot be overstated. Drug development companies invest billions of dollars to hopefully bring a drug to market, so it makes sense they would want to shorten the development time and, therefore, overall cost. There can be a considerable financial strain to meet development guidelines and other benchmarks.
Regarding cancer mortality and studying drugs in a prognostically poor patient population, improving initial cancer detection methods has been proven to significantly increase overall survival time. Technologies such as the positron emission tomography (PET) scan can radically improve patient-important endpoints in clinical trials such as overall survival and progression-free survival.
From a financial perspective, implementing a clinical research organization (CRO) can considerably improve the efficiency, scalability, and overall success of an expensive oncology clinical trial. While utilizing a CRO is an investment, some CROs can provide global clinical trial support and expertise in the fields of pharmaceuticals, biotechnology, and medical devices that can prove to be invaluable.
Study Design Flaws
Even if an oncology trial has infinite money, resources, and a perfectly designed therapeutic, none of that matters if the study is not designed correctly. Due to the complexity of cancer, there are many pitfalls and biases present in oncology study design.
Unbalanced or underrepresented demographics comprise many of these flaws. For example, a study may include two cohorts, one with an average Eastern Cooperative Oncology Group (ECOG) performance status of one and another with an average ECOG status of four.
The group with an ECOG score of one is fully ambulatory with slight physical activity restriction, while the other group with an ECOG score of four is completely disabled and bed-bound. While usually not as blatant or obvious, demographic differences like this can severely bias a study’s results.
Underrepresented patient demographics comprise an entirely different aspect of study design flaws. While not inherently an actual study flaw, poorly or underrepresented patient special populations or groups can lead to poor external validity, or the extent to which the study results can be generalized to other contexts. In oncology studies, in particular, older adults are commonly underrepresented due to a variety of factors, including too broad inclusion criteria to meet recruitment benchmarks.
Defined hypotheses and accurate statistical modeling should be established prior to study initiation. For example, some studies that evaluate a specific cancer type such as breast cancer, prostate cancer, or lymphoma may not control for environmental factors.
Studies often attempt many different solutions to address these problems preemptively. Strict inclusion criteria and follow-up screening, matched analysis, and propensity score-based weights are possible solutions to mitigate these types of flaws.
Recruitment Issues
Interventional studies in oncology, like any other major disease state, require the successful recruitment of adequate, representative participants. Some studies, unfortunately, estimate only 55 percent of clinical trials achieve the trial’s original specified goal sample size. Successful recruitment is pivotal to any oncology trial’s success.
Many factors affect recruitment success. Trial availability in an area with low potential participant population density can be challenging if there simply are not enough participants with the type of cancer being investigated. This holds especially true if it’s a rare type of cancer like some forms of carcinoma and leukemia. Additionally, limited site access, patient concerns, and low provider willingness to participate in the study intervention can dramatically decrease proper recruitment success.
Some successful recruitment strategies commonly performed include telephone reminders to non-responding participants, opt-out procedures requiring direct communication with the research team, financial incentives, and making trials open instead of blind.
Statistical Interpretation
Like study design flaws, the poor implementation or interpretation of statistics can single-handedly derail a clinical trial. Researcher errors causing misuse or misinterpretation of statistics can impair a study’s scientific validity.
Common mistakes in interpreting study statistics include poor p-value interpretation, assuming association versus causation and vice versa, and reporting biases. In addition to improving the efficiency and logistics of running a study, CROs can often perform clinical data management to ensure statistics are utilized appropriately and help reduce the risk of human error.
Surrogates Versus Event Endpoints
Applying surrogate endpoints in clinical research is a tactic that has benefits and detriments compared to event endpoints. Surrogates are especially common in oncology research when full event endpoints such as overall survival, progression-free survival, and quality of life improvement are not always feasible from a time and money perspective.
In oncology studies, surrogate endpoints can be something as simple as “percentage tumor shrinkage” or the reduction in a circulating blood marker known to be related to the cancer-drug interaction. While still clinically useful, surrogate endpoints intended to be used to extrapolate actual event endpoints may not be true indicators of a drug’s true efficacy despite their convenience.
When Should I Consider a CRO?
While there is constant innovation in the field of oncology, cancer cases continue to rise. The American Cancer Society reports that in the year 2022, there will be nearly 1.9 million new cases of cancer, leading to more than 600,000 deaths. Clearly, there is still a tremendous need for improved cancer therapeutics.
However, bringing an oncology intervention to market can be an immense task. Utilizing a CRO can make the difference between market approval and market withdrawal due to inefficacy or safety concerns.
At iProcess Global Research, you can expect exceptional teams and operations to provide cutting-edge research to help organizations with their clinical trials. With constant demand for clinical trials, iProcess continues to meet the demand for specialists who can provide the high level of quality and competence required.
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