6 Things You Must Consider When Designing a Successful Preclinical Study in Oncology

Preclinical studies are essential for advancing oncology drug development programs. They provide valuable insights into a drug candidate’s safety and efficacy before it moves into clinical trials. A well-designed preclinical study can increase the likelihood of success in clinical trials, saving time and resources in the long run. In this article, Noble Life Sciences will discuss the six elements of a well-designed preclinical study and provide tips on how to optimize study design for success in oncology drug development.

1 – Define Clear Study Objectives

The first step in designing a preclinical study is to define what you’d like to achieve clearly. This involves identifying the specific research question(s) that the study will aim to answer, usually involving safety, efficacy, and/or mechanism of action. Defining clear study objectives helps ensure that the study is focused, and the data collected are relevant to the overarching research question. Having well-defined objectives is especially crucial in oncology drug development, as there are often multiple indications or patient populations that may benefit from a drug candidate’s therapeutic effects. For example, a company may have a drug candidate that targets a specific molecular pathway in cancer cells, thus one of the preclinical study’s objectives should be to evaluate the expression levels of key proteins in that pathway to confirm the candidate’s mechanism of action. Similarly, another objective could be to determine if the drug is effective in reducing tumor growth in mouse models of breast cancer or melanoma and if the affected pathway has been shown to play a role in those cancers. Objectives should be specific, measurable, achievable, relevant, and time-bound (SMART) and should outline the research question, the research population, the methodology, and the expected outcomes. By defining these parameters in advance, researchers can develop a clear roadmap for their study, identify potential challenges, and allocate resources effectively.

2 – Define Relevant Endpoints

Endpoints are the specific measurements that are used to assess the study’s outcomes. For example, in a preclinical study the endpoints could be evaluating whether the drug decreases tumor volume, lengthens time to tumor progression, or increases overall survival rates. It’s also critical to define the primary vs. secondary endpoints. The primary endpoint for a preclinical oncology study could be to assess whether the drug shrinks a tumor by a certain percentage, while secondary endpoints could include evaluating PK/PD, biomarker expression levels, and the percentage of tumor-infiltrating lymphocytes or the level of cytokines produced by immune cells.

3 – Choose Appropriate Animal Models

Selecting the appropriate animal model is imperative to the success of a preclinical study. It is crucial to select a model that closely mirrors the disease characteristics of the human condition under investigation. For instance, a company focused on developing immunotherapies for lung cancer might choose to use a mouse model that expresses human tumor antigens to evaluate the drug’s efficacy in boosting the immune system’s response to cancer cells. Conversely, the company could opt to utilize a genetically engineered mouse model that spontaneously develops lung cancer, depending on the research question.

4 – Optimize Dosing Regimens

Dosing regimens should be optimized to ensure that the drug candidate is administered at the appropriate dose and frequency to achieve the desired therapeutic effect. This may involve testing multiple dose levels and delivery routes (oral, IV, Sub-Q, etc.) to determine the optimal dose-response relationship and select the appropriate dosing route.

5 – Ensure Statistical Power

Statistical power refers to the ability of a study to detect a true effect. A study with high statistical power is more likely to detect an actual treatment effect, while a study with low power may fail to identify a real effect, leading to a false negative result. In oncology preclinical studies, it is critical to ensure that the sample size is determined based on the expected effect size and projected variability in the data. For example, a company may conduct a preclinical study to evaluate a drug’s effect on tumor growth in mouse models of pancreatic cancer. The study’s statistical power may be determined by considering the expected effect size and variability in tumor growth rates in the mouse model. While a higher statistical power increases the chances of detecting meaningful treatment effects, achieving high power may require larger sample sizes, which can be costly and time-consuming. Balancing power, sample size, and available resources are all important considerations in preclinical study planning.

6 – Consider Regulatory Requirements

Companies need to consider regulatory requirements when designing preclinical studies in oncology drug development, as they may vary depending on the intended use of the drug candidate and the target patient population. For example, regulatory authorities may require specific safety or efficacy endpoints to be met before a drug candidate can move into clinical trials. Companies should consult with regulatory experts early in the planning process and stay up to date on regulatory guidelines to ensure that their preclinical studies meet regulatory requirements.


In conclusion, designing preclinical studies for success in oncology drug development requires careful consideration of study objectives, endpoints, animal models, dosing regimens, statistical power, and regulatory requirements. Taking the time to apply these principles and carefully optimize study design can greatly enhance the chances of success in oncology preclinical programs. By partnering with an experienced preclinical contract research organization such as Noble Life Sciences, companies can leverage specialized expertise and state-of-the-art facilities to accelerate their drug development programs into the clinic faster.



Scientific Advisor Team

Our oncology team is committed to fight The Fight

by advancing your preclinical research.

Stephen K. Horrigan, Ph.D.

Stephen K. Horrigan, Ph.D.

Chief Scientific Officer

Pang-Kuo Lo, Ph.D. MSc

Pang-Kuo Lo, Ph.D. MSc

Team Lead, Assay Development

Arundhati Ghosh, Ph.D., MSc

Arundhati Ghosh, Ph.D., MSc

Study Director

Yongping Chen, M.D., Ph.D.

Yongping Chen, M.D., Ph.D.

Senior Study Director

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