2024 Archives

Navigating Dose Optimization in Drug Development: Answering Questions about Project Optimus

In the complex world of drug development, dose optimization plays a crucial role. Project Optimus, a groundbreaking initiative, focuses on refining this process for the development of oncology drugs.

During our recent webinar, we received dozens of questions about this new paradigm in oncology drug development. This blog post highlights some of those questions and answers from our expert speakers.

How critical is the biomarker-clinical efficacy relationship in choosing the minimum effective dose?

While the biomarker-clinical efficacy relationship is vital, it’s important to acknowledge that most biomarkers do not act as surrogate endpoints, meaning they don’t necessarily predict clinical efficacy. Instead, a more pragmatic approach is to treat biomarkers as indicators of target engagement. By doing this, we can use the biomarker response as support for the clinical response observed in the trial. Ideally, the biomarkers measured in Phase 1 should measure this target engagement as directly as possible.
Additionally, pharmacodynamic (PD) endpoints are very useful (in conjunction with clinical response data) in defining the dose range to be studied in Phase 2. Typically, two doses are chosen — one that maximizes the biomarker response and a higher dose to address any uncertainties about the drug’s mechanism. Although this strategy isn’t flawless, it is currently one of the best approaches available.

What are your recommendations for measuring and analyzing biomarkers to select an appropriate dose? What sampling timings are recommended?

The ideal biomarkers directly measure target engagement and should have some correlation with a positive response in animal models. Choosing appropriate biomarkers is challenging and should involve collaboration among clinical pharmacology, translational medicine, and clinical teams.

Sampling timing is crucial. Many biomarkers lose their utility due to insufficient sampling. For instance, measuring biomarkers only after the first dose can miss long-term changes. Early involvement of clinical pharmacology or pharmacometrics teams can ensure that biomarkers and sampling schemes are optimally selected.

How should investigational therapies with a myriad of biomarkers still being studied in Phase 1a/b be evaluated?

This situation is complex and depends a great deal on the target of the investigational therapy. Ideally, biomarkers should directly measure target engagement and be chosen thoughtfully, involving input from pharmacometrics, translational medicine, and clinical teams. It’s better to focus on one or two well-selected biomarkers rather than several chosen without careful consideration.

Could you explain the concept of “short half-life”?

The term “short half-life” is relative to the dosing interval. For instance, a drug with a 30-day half-life would not be considered short in most cases. However, if the drug is dosed annually, a 30-day half-life would be relatively short, suggesting no accumulation of the drug.

A more concrete definition of “short” could be a half-life that results in no accumulation for a specific dosing regimen. For example, a drug with a 4-hour half-life administered weekly would generally not accumulate, and pre-dose values would be zero. In such cases, collecting pre-dose samples would be redundant and post-dose samples would be more informative.

What are the advantages of conducting studies in healthy subjects for small molecule targeted therapies versus starting directly in patients?

Conducting small studies in healthy volunteers (HVs) can provide critical information on the drug’s exposure and half-life in humans, aiding in the design of patient studies. Additionally, safety profiles can be more clearly distinguished in HVs.

However, investors might prefer patient data over HV data. A compromise could be a two-part study, beginning with HVs and followed by patients, allowing for initial pharmacokinetics (PK) knowledge while ultimately providing patient data, which is more compelling to stakeholders.

Most often though, early oncology studies are conducted in patients, so as not to expose volunteers with healthy body systems to potentially toxic treatments.

What does minimal overlap in PK exposure translate into, especially in accelerated titrated designs when there might be insufficient information on PK variability?

The key factor here is the inter-patient variability in clearance. If there is uncertainty about the variability estimate, simulating various estimates can help determine the minimal overlap. For example, if variability ranges between 25% and 45%, simulations using these estimates can guide dose selection to minimize overlap, considering safety and other factors.

By addressing these questions, Project Optimus aims to refine dose optimization strategies, ultimately improving the effectiveness and safety of new therapies.

Interested to learn more? Join our office hours on Project Optimus with James Matcham and Michael Fossler on September 18 — sign up today!

SAS vs. R in Clinical Development

With more than 18 years of experience in the clinical research industry, I have worked extensively with SAS. However, in recent times, R has emerged as a groundbreaking tool in data analysis. In this article, I compare the use of SAS and R in clinical development, aiming to determine which tool might be the best fit to meet our requirements.

Simulating Survival Outcomes for Unanchored Simulated Treatment Comparisons: Guidance on Censoring Approaches

Unanchored simulated treatment comparisons (STCs) are a valuable tool for manufacturers navigating the health technology assessment (HTA) landscape. When head-to-head clinical trials are unavailable, STCs allow for population-adjusted indirect comparisons between a single-arm trial and an external control arm.

Using regression modeling to predict outcomes based on patient characteristics, STCs enable comparisons in the absence of a common comparator. This is particularly valuable when evaluating novel therapies, especially in rare or specialized disease areas where randomized controlled trials may be limited.

Career Perspectives: A Conversation with Stephanie Brandt

In this latest edition of the Career Perspectives series, we are excited to introduce our readers to Stephanie Brandt, Senior Corporate Counsel at Cytel.

Can you give us a background on your career and your professional journey so far? What made you choose to practice corporate law?

Many years ago, I began my legal career as a law clerk for a judge in the New Jersey Appellate Courts. When I relocated to North Carolina more than ten years ago, I entered the life sciences industry and found myself at a wonderful company. There, I not only learned the ins and outs CRO services but also developed my skills as an in-house commercial attorney. I joined Cytel in late 2021 with a goal of expanding my in-house corporate legal experience and using my existing skillset to make an immediate positive impact.

Given that many of our employees supporting our business operations do not come from a medical or pharmaceutical background, what made you decide to pursue a career in this industry, and specifically at Cytel?

A friend taught me a bit about the industry, and it intrigued me because it rekindled my interests in biology and public health from my undergraduate days. I had a basic understanding of life sciences and the fundamentals were not foreign to me, but learning about the full impact our work has on people’s health and lives is amazing; I am happy to play a supporting role.

What is your role at Cytel, and what do you like best about it?

As corporate counsel, a fundamental aspect of my role is to help protect Cytel from risk, ensure compliance, and balance these with our goals of being a profitable company and delivering quality for our customers. The people I get to work with are definitely my favorite part of this job. I work with a wonderful legal team, whom I respect and have fun with, and I get to support people throughout the organization on a variety of challenges. Additionally, I get to be creative in my role, and no two days are the same, so I am always learning.

We operate in an industry where compliance is critically important. How does Cytel prioritize legal compliance and ethical standards in its operations?

The Cytel legal team prioritizes compliance by working with the various business functions to help build out and continuously evolve our compliance programs. We also negotiate compliance standards with our clients and ensure that Cytel can adhere to the terms and conditions in our contracts. The more Cytel expands globally, the more complex and comprehensive our compliance programs need to become.

As Senior Corporate Counsel, can you walk us through a typical day in your role?

My day typically revolves around prioritization (and re-prioritization), with commercial contracting taking up the majority of my time. I review contracts for Cytel’s EVA, DMC and FSP business units, as well as vendor contracts and HR/corporate agreements that require review. In addition to contract review, I respond to escalation issues, including quality events, audit issues, or special projects like integration efforts for our newly acquired affiliate companies. Internal meetings, combined with meetings with clients or vendors to discuss contracting issues make my days fly by.

Which skills do you think are crucial to your function?

Communication skills are critical. Whether it is composing an email to a client or hopping on the phone to figure out how to handle a problem, being able to communicate effectively is a huge help in this role. Also, being able to prioritize and re-prioritize tasks is essential, since the day never seems to unfold the way you think it will.

In your three years at Cytel, you have worked on many projects. Can you share which project(s) you are the proudest of, and why?

I probably cannot give many meaningful details of the projects I am most proud of, but I can say that there have been some projects that really required perseverance to see through to the point of getting positive results, and that is very satisfying. Also, being able to collaborate with colleagues in other departments to get results is very rewarding and fun.

You recently won an Employee Spotlight Award. Could you describe the exceptional work that led to this recognition and how receiving this award impacted you?

The Spotlight awards are based on Cytel’s core values, and my work was recognized for “Center on the Client: my commitment to understanding and meeting our clients’ needs to enhance their satisfaction and loyalty” which is something I strive to balance and achieve daily. Being recognized for this effort is very humbling and I am proud of the work we do to support Cytel. I try to be proactive about figuring out solutions to client contracting issues; however, we have to balance client satisfaction with our compliance concerns and stick with our processes which are in place to protect not only Cytel but our clients as well.

How do you see the role of legal counsel evolving at Cytel, as the company continues to grow and innovate?

The legal team at Cytel is small but mighty, and as Cytel grows we strive to be able to continue to serve our whole organization. In order to do that we need to always have an eye on increasing efficiency. Technology such as AI is ever evolving, and we want to be at the forefront of it and not playing catch-up.

As an employee who works full-time from home, what are your strategies to keep a healthy work-life balance? Do you feel supported in this by Cytel?

I do feel that Cytel gives me the tools to maintain a balanced life, even though sometimes that is easier said than done. I have two young boys at home so I’m busy all week long, whether it’s the school year or summer. I try to take a gym break daily and work out, which I find keeps me sharp and lowers my stress. I really value being able to work from home, the time it saves and the flexibility it provides. I used to commute daily into the city for work and while that was worth it at the time, I make good use of that hour or more I get back each day by working from my home office, and I feel no less connected to my team and colleagues even though we are chatting on the computer.

What advice would you give young, aspiring women interested in a legal profession in the biotech and pharmaceutical industries?

There are a lot of great opportunities in this domain and there is much to learn. I think it’s important to always be willing to work harder than the next person, give your best effort, and always keep learning.

What are your main interests outside of work?

I am an avid reader which really helps me unwind and relax. I love to cook too, which is helpful because the people in my house love to eat. I live on the coast so on most weekends when the weather is warm our family is out enjoying the beach and the ocean. We have not travelled as much in the last few years, with covid and having young kids, but we love visiting the mountains and hiking in the summer, taking in the fresh mountain air and the views.

Understanding the Critical Role of DMCs in Oncology Studies

In clinical research, particularly within oncology, Data Monitoring Committees (DMCs) play a pivotal role in ensuring the integrity and safety of clinical trials. With the high volume of oncology studies and the extensive use of DMCs in these trials, it is essential to understand the specific nuances and challenges these committees face. Here, I provide an overview of the critical aspects of DMCs in oncology studies.

Oncology Clinical Trials: Design Trends in Biomarker Research

Oncology research has seen many changes and advances in recent decades, from new therapies in combination with backbone chemotherapy to novel treatments targeting malignancies, and compounds targeting specific disease biomarkers at the genetic mutation level. The latter approach has called to question large, relatively long clinical studies assessing the safety and efficacy of treatments against a large population defined at the tumor level. Rather, research at the subpopulation or biomarker level has garnered much more interest as targeted treatments are being developed.

This focus on subpopulations and biomarkers is changing how researchers approach clinical trials in oncology and helps resolve several issues with larger clinical trials. For example, treatment effects may be diluted in a heterogeneous population, possibly resulting in an underpowered study. Furthermore, a large trial in a heterogeneous population may place patients for whom the drug is ineffective at risk of serious adverse events. On the other hand, restricting enrollment to a target subgroup without sufficient evidence may deny a large segment of the patient population access to a potentially beneficial treatment. This blog post will briefly introduce two statistical approaches addressing the rise of more specific study populations: predefined subpopulation statistical analysis in the context of a larger trial population and population enrichment of the more promising subgroup within an ongoing study.

Subpopulation Analysis

Subpopulation testing and analysis is a phase III clinical trial design strategy in which a subset of the study population is selected based on patient characteristics that may be more likely to respond to the treatment under investigation. Identifying and analyzing specific subpopulations allows the researcher to explore whether a treatment leads to different effects in a pre-designated subpopulation. A subpopulation can be defined by any stratification characteristic such as gender or geography, and in oncology clinical trials, specific biomarkers identified within a study population.

This type of approach to clinical research has several significant benefits in Oncology studies:

A large trial in a heterogeneous population may place patients for whom the drug is ineffective at risk of serious adverse events.

In a heterogenous population, the treatment effect may be diluted, possibly resulting in an underpowered study.

Restricting enrollment to the targeted subgroup without sufficient statistical evidence of lack of efficacy in the non‐targeted subgroup may eliminate beneficial treatment options for patients.

Subpopulation analysis allows for treatment recommendations based on individual characteristics.

As with any novel adaptive design approach, subpopulation analysis requires several considerations at the design stage. These considerations include the specific definition of the subpopulations for analysis in the study, the appropriate timing for an interim analysis, the methods used for hypothesis testing and type-1 error preservation, and the sequence of hypothesis testing of the different subpopulations and/or the full study population.

With these considerations in mind, rigorous planning and testing in the design stage of such a clinical trial is critical. Cytel’s East Horizon adaptive clinical trial design software offers a unique solution for the planning and testing of a clinical trial design that includes subpopulation analysis. In Cytel’s solution, hypothesis testing for the full and subpopulations can be performed using graphical multiple comparison procedures (gMPC) with a weighted Bonferroni procedure employed for closed testing. This method of hypothesis testing uses directed, weighted graphs where each node corresponds to a single hypothesis. A transition matrix is used as a complement to specify the weights and generate an intuitive diagram. Finally, a simple algorithm sequentially tests the individual hypotheses using the specified weights and hierarchies.

Population Enrichment

Population Enrichment is an adaptive clinical trial approach that includes the prospective use of any patient characteristic to obtain a study population in which detection is more likely than in the unselected population. There are two types of population enrichment: Prognostic Enrichment, in which a high-risk patient population is identified based on a biomarker, and Predictive Enrichment, in which the researchers identify a patient group more likely to respond to treatment. Some industry trends that have contributed to the popularization of this adaptive design method include the soaring costs of clinical trial execution, a move away from a “one-size-fits-all” approach to clinical development, and the rising interest in individualized medicine. This adaptive design approach has several benefits, including the identification of highly responsive patient populations, the efficient detection of a treatment effect in a smaller sample size, and the ability to identify beneficial treatments for a subgroup of patients that may have failed with a broader population in a more traditional study design.

Population enrichment can be seen as an extension of the sample size re-estimation (SSR) methodology, which we discussed in more depth in a previous blog post.

In the enrichment adaptive approach, a pre-specified number of subjects comprising the entire population, designated as cohort 1, is tested in an interim analysis, and a data monitoring committee reviews the results to assess efficacy or futility against predetermined thresholds. Suppose the analysis shows promising results for only a specific subpopulation of interest in the study, this population is “enriched” with additional patient enrollment in the remaining number of subjects of the study, designated as cohort 2, to enhance data collection for only this subgroup of interest and increase the overall probability of success of the study. As with any adaptive approach, this method has specific considerations, including closed testing with a p-value combination, the preservation of type-1 errors, and additional special considerations requiring attention in event-driven trials like most oncology ones.

Final Takeaways

Both subpopulation analysis and population enrichment are adaptive approaches to modern trial designs in oncology that offer great hope for researchers and patients alike. As the focus on specific patient populations narrows, these adaptive design types are gaining industry traction. Software-guided clinical trial design and simulation using tools such as East Horizon ensure adaptive elements are incorporated thoughtfully and are rigorously tested prior to trial launch.

Learn more about these approaches in our upcoming webinar ‘’Oncology Clinical Trials: Design Trends in Biomarker-Driven Research’’ with Boaz Adler and Valeria Mazzanti.

External Validity Bias in HTA Submissions: A Case for Transportability Methods

Health technology assessment (HTA) bodies support decision-making for the reimbursement of new technologies at the local or national level. Recommendations made by HTA bodies are based on various sources of evidence, ranging from the preferred standard randomized clinical trials to real-world data (RWD) when trials are unavailable or not relevant to the target population of the decision problem. Non-randomized studies of treatment effects are already widely used in rare diseases and innovative technologies to contextualize findings from single-arm trials. Watch our recent webinar on real-world external control arms here.

To build trust in the evidence that supports decision making, researchers need to understand and address potential risks to study validity.

Opportunities and Pitfalls of Using AI/ML in Clinical Development

The future of clinical development is set for significant change, driven by the integration of new digital data sources, advanced computing power for detecting meaningful patterns using artificial intelligence (AI) and machine learning (ML), and increasing regulatory support through new collaborations.[1] The United States Food and Drug Administration (FDA) has noted a significant increase in the use of AI/ML in drug development, with over 100 submissions in 2021 alone.[2] These submissions cover the entire drug development process, from drug discovery and clinical research to post market safety and advanced pharmaceutical manufacturing. Here, however, we concern ourselves with how AI and ML approaches can impact the way clinical trials are designed, conducted, and analyzed, offering potential enhancements in efficiency, reduced costs, and improved patient outcomes.

In this article, I explore the opportunities and challenges of AI/ML in clinical development, particularly in the context of Cytel’s operations.

Artificial Intelligence Applications in HEOR

Written by Reza Jafar, Omar Irfan, and Maria Rizzo

Recent advancements in machine learning (ML) and artificial intelligence (AI) can offer tremendous potential benefits to health economics and outcomes research (HEOR), such as in cohort selection, feature selection, predictive analytics, causal inference, and economic evaluation.[1] The use of ML and AI has been previously explored in systematic literature reviews (SLRs), real-world evidence (RWE), economic modeling, and medical writing.[2-4]

In this article, we assess the evolving landscape of evidence and developments attributed to AI in HEOR, reflecting on recent insights and developments presented at the 2024 US conference for The Professional Society for Health Economics and Outcomes Research (ISPOR) in Atlanta. Read more »

The Role of External Data in Oncology Drug Development

Randomized controlled trials (RCTs) remain the gold standard for the evaluation of the safety and effectiveness of a new treatment. However, in a number of cases alternative approaches leveraging external data (i.e., data from outside of a clinical trial) — ranging from single arm trials to augmented RCTs — can be appropriate. Here, we discuss how to leverage and incorporate external data in drug development, focusing on the use of external control arms and Bayesian borrowing.

Newer Posts

Older Posts

Discovery

Phase I-III Clinical Trials

Commercialization

Real-World Evidence Solutions

Clinical Trial Design

Trial Delivery

Advanced Analytics

Specialty Areas

Strategic Consulting

Beyond Functional Service Provider

Project-Based Analytical Solutions

Trial Design Software

Trial Implementation and Decision Support Software

LiveSLR® Software for Systematic Literature Reviews

Our Solutions

Quick Links

Quick Links

Quick Links

Quick Links

Quick Links

Quick Links

Quick Links

Quick Links

Quick Links

Quick Links

Quick Links

Quick Links

Quick Links

Quick Links

About Us

Quick Links

Insights

Quick Links

Careers

Quick Links

How critical is the biomarker-clinical efficacy relationship in choosing the minimum effective dose?

What are your recommendations for measuring and analyzing biomarkers to select an appropriate dose? What sampling timings are recommended?

How should investigational therapies with a myriad of biomarkers still being studied in Phase 1a/b be evaluated?

Could you explain the concept of “short half-life”?

What are the advantages of conducting studies in healthy subjects for small molecule targeted therapies versus starting directly in patients?

What does minimal overlap in PK exposure translate into, especially in accelerated titrated designs when there might be insufficient information on PK variability?

Subpopulation Analysis

Population Enrichment

Final Takeaways