Three specialists – Dr. Sarah Blagden, Associate Professor of Medical Oncology, University of Oxford; Maria Prendes, Head of Oncology at the Covance Biomarker Solution Center; and Kamal Saini, Senior Medical Director of Oncology at Covance – recently discussed this highly relevant topic in an educational webinar, which is now available as anon-demand recording。
This article shares some of the highlights of the well-attended webinar that covered the role of biomarkers in accelerating drug development timelines, the benefits and limitations of biomarker analysis and the characteristics of novel trial designs.
Accelerating Drug Development Timelines with Biomarkers
There is a clear notion in drug development: Many anti-cancer treatments are directed towards a specific population of patients, and may benefit among them, only those patients with a histologically/molecularly defined cancer. While biomarkers offer clear benefits during the drug development process, they also present some limitations. Obvious benefits include among others, eliminating the burden of treating patients who will not respond to a therapy (basing the judgement on the presence/absence of a specific predictive biomarker); or identifying mechanisms of acquired resistance to a particular therapy (introducing new possibilities for combination therapies with other therapeutic agents). Therefore, early-at-risk investment in biomarker development leads to compounds with better patient outcomes and stronger cases for reimbursement, while accelerating and making more efficient the drug development process.
临床biomarkers also pose some limitations, they require time and resources. In general terms, the drug development process and the biomarker identification occur simultaneously, but in reality, biomarker development often lags behind drug development: The majority of the efforts are applied to developing the new anti-cancer agent and subsequently, identifying biomarkers with predictive, prognostic and pharmacodynamic value for the therapy. However, there is an urgent need in a clinical trial to identify robust biomarkers as early as possible in the clinical development program. Otherwise the confidence in a putative biomarker performance may be insufficient to restrict the treatment of a new agent to a subgroup of biomarker-positive patients, delaying the drug development timeline.
早期识别强大的生物标志物
Extracting the greatest value of a predictive, prognostic or pharmacodynamic biomarker requires identifying it as early as possible in the clinical development process.
Prior to utilizing a patient’s biomarker information in clinical practice, the biomarker should demonstrate鲁棒性, with both analytical validity (answers the question whether or not we should trust the results of a specific biomarker), and clinical validity (the results obtained from the test should be related to other clinical information), as well as clinical utility (a particular biomarker should be ultimately useful to improve a patients’ health).
当辩论哪个测试可以用作临床环境中测量生物标志物的平台时，我们需要考虑这些测试可以开发并验证为“适合目的”：从探索性目的到包含/排除标准的范围（初级/临床试验中的次要目标和终点）。
As a potential biomarker for stratification of patients is discovered, identified and characterized in the early drug development phase, its clinical fitness must also be evaluated to understand its robustness before it can support commercialization. Aligning the market authorization of the drug with approval of the biomarker test is paramount to avoid delays in clinical drug development.
了解自适应试验设计的作用
There are different strategies to incorporate biomarkers into the clinical study design. These strategies have been previously classified asenrichment strategiesand分层设计。在过去几年中，第三组生物标引导治疗策略包括普遍存在的普遍存在adaptive designs.
In 2010, the U.S. Food and Drug Administration defined an adaptive design as a study that includes a prospectively planned opportunity for modification of one or more specified aspects of the study design and hypothesis based on analysis of (usually interim) data from subjects in the study.
基于临时分析对设计的适应包括：
- Adding or dropping treatment arms
- Changes in the required sample size
- 分配的研究人群比例的变化，以便随机化更多患者治疗武器，这些武器正在做得更好
- Refinement of the existing study population according to their predictive biomarkers
在实现自适应设计期间的最常见的适应是指生物标志物定义的子组内随机化概率的变化或丢弃生物标记定义的子组。
Adaptive designs constitute a fundamental alternative in the精密医学时代，允许在审判过程中灵活性。这种类型的设计表明了成本效益，并最大限度地减少了达到认真成果的所需时间（尽管有时在筛选的受试者的数量中增加）。除了提供更有效的治疗方面对患者进行更良好的道德，它还避免了错误的结论。
自适应设计为临床试验提供了良好的替代品：
- The candidate biomarker is not known at the beginning of the trial
- There are multiple experimental treatments and pre-specified biomarker-defined subgroups
- Existence of well-stablished analytical validity
- Rapid turnaround time for biomarker assessment
In conclusion, the efficiency of a trial design is measured by the increased power of the study and the minimized required sample size or duration. Biomarker-driven adaptive design trials play an important role in reducing the cost and increasing the clinical utility of trials evaluating biomarker-guided treatment strategies.
Exploring complex innovative design (CID) trials
由于生物标志物的使用导致分段化的分子定义的亚步骤，因此对培训设计更加需要纳入生物标志物，统计和技术的进步，以解决癌症药物发育的效率。如讨论的那样hadley等。Cell文章，具有全面且集成的分子分析的多OMICS方法可以导致各种人类癌症的分子关系的定义，并具有癌症治疗试验的潜在临床效用。
Complex innovative design (CID) trials terminology comes from a U.S. FDA program that started in 2018 and runs until 2022 with the intent of advancing and modernizing drug development. A CID emphasizes the use of external data or the real-world data. It can include pre-specified adaptations to multiple aspects of the study, adaptive or Bayesian designs that require simulations. A CID trial focuses on the patient benefit and filling a gap where new therapies are needed for underserved patient populations.
超越美国，监管机构在试验设计中鼓励创新和复杂性。欧洲医学署（EMA）和MHRA都表明，监管角度倾斜，有利于尽快尽快尝试新的创新，并将CID作为癌症研究平衡组合的一部分。
Watch the on-demand webinarto hear more about biomarkers, with a case study describing a Phase III study design strategies based on biomarkers and recent examples of overcoming hurdles in conducting Complex Innovative Design (CID) studies.
