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Craftsmanship in Clinical Trial Study Design

Posted by Brook White on Wed, Jul 06, 2016 @ 02:55 PM
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Ryan Bailey, Senior Clinical ResearcherRyan Bailey, MA is a Senior Clinical Researcher at Rho.  He has over 10 years of experience conducting multicenter asthma research studies, including the Inner City Asthma Consortium (ICAC) and the Community Healthcare for Asthma Management and Prevention of Symptoms (CHAMPS) project. Ryan also coordinates Rho’s Center for Applied Data Visualization, which develops novel data visualizations and statistical graphics for use in clinical trials.

Shann Williams, Senior Director OperationsShann Williams has 10 years of experience managing clinical trials. She is a Sr. Director of Operations and the program director of the statistical and clinical coordinating center of the Transplantation Group for the division-wide consolidated coordinating center sponsored by the National Institute of Allergy and Infectious Disease (NIAID).  In addition, Shann serves as Rho's project management operational service leader, an internal expert sharing project management best practices, processes and training.

My dad is an expert carpenter and handyman. Growing up, I spent hours watching him work - furniture, flooring, painting, plumbing, roofs, siding, decks - you name it, he did it. I learned a lot from watching him and helping him, but I never accomplished his level of expertise and proficiency. It is not for lack of knowledge or ability; rather, it is a lack of practice and experience. I'm capable. My father is masterful.

craftsmanship in clinical trial study designClinical trials are not so different from construction and craftsmanship. To be a successful clinical researcher, you need to coalesce expertise across a variety of domains - statistics, data management, project management, clinical operations, product safety, regulatory, medical writing - as you design, prepare, execute, and troubleshoot throughout the trial. The CRO industry exists because we provide specialty expertise in these areas, and many pharmaceutical companies are glad to have a trusted partner to manage various aspects of this work.

Yet, regardless of which CRO services pharmaceutical companies seek out, one task pharmaceutical companies have been reluctant to source to their CRO partners is clinical trial design. According to a recent press release by Cutting Edge Information, as recently as 2014, no Top 50 pharmaceutical or medical device team surveyed reported that they shared clinical trial design responsibilities with CROs.

This is not especially surprising. With their product on the line, pharmaceutical companies have a keen interest in retaining careful control over the study design. It is also a matter of practicality. Before seeking out a CRO to support management of your trial, it helps to have a well-constructed plan of how the trial should be executed. However, Cutting Edge Information reports that this trend is likely to change dramatically in coming years. By 2020, over 50% of companies they surveyed plan to share trial design responsibilities with CROs. Why the change?

In part, it's due to the need for craftsmanship. When it comes to clinical trials, CROs offer a level of end-to-end proficiency built on decades of extensive trial management experience and specialization. When your job is conducting hundreds of trials for a wide range of clients and diverse therapeutic areas, you naturally achieve a high degree of expertise: a deep knowledge base, valuable foresight, honed skills, improved efficiencies, and the ability to operate deftly in a complex and highly regulated environment. As the ones most often implementing the trials, overseeing the day-to-day project operations, and conducting analyses, CROs are in the best position to identify the strengths and weaknesses of clinical trial designs.

With the pace of new drug and device development lagging, costs increasing, and pressure to get efficacious products to market building, clinical trial designs have come under growing scrutiny. Bad blue prints lead to less than optimal functionality or worse: a complete do-over. In the same way, even simple trial design errors will lead to less than optimal results. The need for a do-over can be cost-prohibitive or just plain disastrous.

By incorporating CROs in the design process, pharmaceutical companies will foster closer partnerships, reduce costs by leveraging efficiencies, benefit from the extensive experience CROs have to offer, and craft more effective trials. Independently, pharmaceutical companies and CROs are capable. Together, we are masterful.

Free Webinar: Protocol Design

Working In Vulnerable Patient Populations: Research in the Cognitively Impaired

Posted by Brook White on Wed, May 25, 2016 @ 11:07 AM
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research in dementia, cognitively impairedResearch involving cognitively impaired patients requires researchers to take extra precautions to protect these patients. There are a number of reasons a patient may be considered cognitively impaired—psychiatric illness, a medical or neurological disorder which may temporarily impair decision making , and dementia to name a few. According to the New York Times, the population of Americans over the age of 65 will nearly double by the middle of the century—a trend which has been referred to as the graying of America. With an increasingly elderly population, more potential research subjects will suffer from various forms of cognitive impairment and there will be a greater demand for treatments for age-related conditions. The likely result is the need to incorporate larger numbers of cognitively impaired patients in research studies.

As researchers, we need to consider how we simultaneously protect patients who are cognitively impaired or may become cognitively impaired during a study with the need to include this population as part of our research. Unlike children, pregnant women, and prisoners, the current Code of Federal Regulations for the Protection of Human Subjects (45 CFR Part 46) does not contain specific guidance for the protection of subjects with cognitive impairment in clinical trials.

Informed Consent

One key issue related to cognitively impaired subjects is informed consent.  Many of the items discussed here are related to consent.  If a research subject has substantial cognitive impairment, they cannot provide informed consent.  In this case, a legally authorized representative (LAR) must provide consent on their behalf.  The standard for an LAR to provide consent is substituted judgment—what is in the best interest of the subject and what would the subject want.  If possible, the subject should assent.  In situations where a subject refuses to provide assent, the subject should generally not be included in the study.

Deciding if a Patient is Cognitively Impaired

Dementia is often a matter of degree, and in mild forms of cognitive impairment, a patient may still be capable of providing consent.  How do we decide when a patient is competent to consent and when an LAR is needed?  This certainly isn’t a settled matter, but one option is to include an assessment which would be performed by the investigator as part of the screening process to make this determination.  The assessment should check the patients understanding of potential risks, potential benefits, that participation is voluntary, and what will be involved in participating (study procedures, additional visits). 

Consent is a Process, Not a One Time Event

In many cases involving dementia, a patient’s decision making ability may degrade over the course of a study.  It may be that a patient is capable of providing informed consent at the beginning of a study, but is not as the study progresses.  This is something investigators should keep in mind.  You may want to plan for reassessment later in the study.

Identifying LARs

There is not a single standard for determining who can act as an LAR.  Some states have enacted laws specifying who can act as LAR, but the laws are not all the same.  In states where there isn’t a law, identifying an LAR can be trickier.  In other countries and cultures, views on who can make decisions for the cognitively impaired vary greatly from common views in the US.  Make sure at the start of the trial that you are aware of local laws and standards related to LARs.

Limiting Risk

Study designs should take extra care in limiting risk exposure in studies which will be using cognitively impaired patients, particularly when there is little or no potential for direct benefit. In most cases, studies involving these patients that don’t offer the potential of direct benefit should be limited to those involving minimal risk.

In conclusion, because formal guidance on conducting clinical research in subjects with cognitive impairment has not yet been standardized or incorporated into law, it is important to take extra care to protect these patients. We’d be interested in knowing how other organizations are responding to this issue. Is this a topic your organization is actively addressing? If so, please share in the comments.

Free Webinar: Selecting Inclusion/Exclusion Criteria for Your Next Trial

5 Tips for Conducting Feasibility for a New Clinical Trial

Posted by Brook White on Wed, Apr 20, 2016 @ 02:12 PM
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Meagan Vaughn, PhD, Research ScientistMeagan Vaughn, Ph.D., Research Scientist,  designs and implements clinical trial feasibility assessments.  She has over 10 years of experience in scientific writing and editing, has authored and contributed to numerous peer-reviewed publications, and serves as a reviewer for several medical and public health journals.  

What does the word “feasibility” mean to you? It may seem like a simple question, but I have found that “feasibility” has many interpretations within the clinical research industry. When we work with a sponsor to conduct feasibility for clinical trial planning, our first task is to figure out what their definition of feasibility is, and more specifically, what questions they are trying to answer.

Most often, the question is “How many sites will we need to meet our enrollment target and timelines for this study?” Of course, this is an important question, but asking this question can be putting the cart before the horse. The foundation of a successful study is a protocol that is both scientifically sound and viable from an operational perspective. Assuming the former has been sufficiently vetted, the first goal of conducting feasibility should be to test the assumptions of the latter. This is the time to think through the logistics for the site and the subject, and consider the protocol requirements that might affect factors like enrollment, retention, and data quality. Use this exercise to formulate questions that will stimulate a dialogue around these issues with potential investigators. For this type of early stage feasibility, you also need to think about the right tool to gather the information needed, and a web-based survey probably isn’t going to cut it if you are looking for thoughtful feedback. This is the time to leverage relationships with investigators and coordinators to have some focused conversations using your questions as a guide for the discussion. More often than not, they will be able to quickly identify potential show stoppers in your inclusion/exclusion criteria, as well as assessments or design elements likely to result in frequent protocol deviations.

Once the feasibility of the protocol has been thoroughly evaluated, the next step is to examine the feasibility of the trial given the constraints of timelines and resources. To this end, a web-based survey can be a quick way to gather data to inform enrollment projections and come up with a list of candidate sites. Below are a few points to consider when crafting a feasibility questionnaire:

  • Asking the right questions is just as important as not asking unnecessary questions.   Stay focused on the key pieces of information needed.  If you aren’t going to analyze it, don’t ask the question.
  • A poorly written question will result in unreliable data.   Consider your audience and have several people review and test the survey before deploying.   For example, consider the question “How long does study startup typically take at your site?”  Without defining the starting point (receipt of the protocol, site selected, or receipt of the regulatory packet), the answers may vary widely.
  • Judicious use of skip logic and display logic in an electronic questionnaire can reduce the burden on respondents and provide cleaner data to the person on the receiving end.   For example, you can use skip or display logic to drill down into specific topics that may only be relevant for some sites (such as regulatory history for sites that have had an inspection).
  • Engage sites in the feasibility process by asking questions requiring their input (e.g., any question that starts with “In your experience…”).
  • Use the right tool to collect information.  At Rho, we use Qualtrics as a survey platform. This platform provides many advantages for conducting feasibility, including:
    • Responsive surveys (skip logic, display logic, survey branching),
    • Piped text (automatically fills in certain fields for sites that have responded to previous surveys), and
    • Real-time reports that can be published to the web for sponsor review

One strategy that we have found to be successful in helping sponsors meet timelines for study startup is to start feasibility and site identification activities under a consulting agreement during the RFP/bid-defense/contracting process. Once a CRO partner has been selected, the team can hit the ground running with site startup activities. This type of early feasibility effort can also facilitate protocol development by gathering site feedback on key operational parameters.

The take home message for feasibility? Spend a little time thinking critically about the key pieces of information that you need that are unique to your project and goals. This will help to hone your feasibility strategy so that you can ask the right questions using the most effective approach.

Protocol Design and Development Webinar: Follow-up Q&A

Posted by Brook White on Thu, Feb 04, 2016 @ 11:07 AM
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Thank you to everyone who attended our recent webinar on protocol design and development.  During the webinar, we weren't able to get to all of the questions.  Below, Dr. Shoemaker and Dr. Kesler have answered the remainder of the questions.

If you didn't have an opportunity to attend the webinar, it is now available on demand.  

Watch Webinar

Why do you think the adoption of the PRM has been so long in the coming?

The Pharmaceutical industry is nototiously slow to adopt novel techniques due to the siloed structure and because the current protocol development process has been in place for decades. Not until the current protocol authors understand the concept of CDISC and the importance of generating consistent data across their program will their methods change. That will only happen if protocol authors are responsible for writing marketing applications.

What are the major consequences of redundancy in the protocol?

Inefficiency due to the need for redundant editing to ensure replacement of all instances and ultimately the cost of amendments if the redundant information is not edited correctly.

How long does it take to properly develop a clinical protocol?

Given adequate time to develop a novel protocol for a new indication with a new molecular entity depends on coordinating the time of all the people whose input is required. Depending upon peoples' priorities and availability it typically takes between one and two months.

If I am developing my drug as an add-on to an approved drug, why not conduct Phase I in patients (not healthy volunteers) taking stable doses of the approved drug? I want to know the safety of a range of doses of study drug when so administered. Pros/cons

Pros are that you save time and money with this approach. Cons are that you won't know if a safety event is due to your product, the approved product, or the combination. You also won't know whether the patients' compromised condition contributed in any way to the safety event.

It is said that no amount of good monitoring can fix a bad protocol. Do you have an example of such a situation and what should the monitoring team look out for to avoid such a situation?

By the time the monitoring team starts reviewing the data at the site or in house it is too late, the die has already been cast by the design of the clinical study. The monitors should endeavor to participate in protocol design to assist in mistakes made at this stage. Otherwise they can only make recommendations to amend the protocol if they see the data being generated is not answering the intended objectives of the study.

Is it advisable to write into the protocol the duration of acceptable periods during which study drug may be suspended without automatically discontinuing the subject?

If your study drug planned to be titrated within subject (e.g. some hypertension drugs) then it is advisable to have not only a duration of suspension, but also dose escalation/de-escalation processes as well. For other situations where study drug is being suspended due to concomitant events, like hospitalization, it is also advisable to have windows for the duration of acceptable suspension. If you don't have expected reasons for suspension and don't expect it to happen often, then it is probably a level of detail you don't need.

Do you have any template?

Yes we have an internal protocol template that we provide to all our clients developing protocols.

Please remind us what data we need to provide for you to determine a sample size for a clinical trial.

It depends on the type of primary outcome. If it is dichotomous, you need to provide the expected percent responding in both the active and control arms. If it is continuous, you'll need to provide the expected mean and variance (or standard deviation) for each group, or the expected difference in means. Other types of outcomes (e.g. survival, multiple categories) require additional information. All studies need a Type I level (alpha) specified as well as the desired power of the study. Estimates of the rate of dropout are also needed for most studies.

We will be conducting another webinar on Thursday March 17th at 1 PM ET on Clinical Research Statistics for Non-statisticians.  We will go into more depth about sample size calculations during that webinar.

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Is this protocol process impacted if/when combo solutions are involved? Combo is defined as drug/sensor based, or subcutaneous drug-illuting solutions.

Not really. Obviously you have to understand the combination product and its properties to the same extent that you understand your drug from a nonclinical and manufacturing properties perspective.

When is unblinded medical review warranted in Phase 2 studies?

There is a new guidance from FDA as of December 2015 advocating the use of a Safety Assessment Committee to review unblinded data from the totality of the data on your product and this should be implemented with the advent of controlled studies in Phase 2.

When can multiple repeat dose safety study be done with parallel dosing of multiple dose groups?

Never. Parallel dosing of multiple dose groups can be done for efficacy comparisons after safety has been demonstrated.

What is the proper endpoint for oncology trial now? it is overall response, tumor shrink, survival or quality of life?

It depends on the type of tumor being studied, but overall response is the preferred SURROGATE clinical endpoint in most cases for accelerated approval with follow-up measurement of survival used to validate this SURROGATE clinical endpoint. Quality of Life is usually montored with one of several patient reported outcomes (PROs) as a secondary clnical endpoint.

You mentiond that CDISC was advising avoidance of the use of "Day 0" terminology to describe intervention date and that this would be required after a certain date. Can you please restate when this goes into effect?

Trials started after December 2016.

Do you know of any company which can offfer to write protocol for their product?

Rho provides protocol design and development services. You can learn more on our website or by contacting us.

Check out our other on-demand and upcoming webinars here.

David Shoemaker, SVP R&DDavid Shoemaker, Ph.D.
Senior Vice President R&D

Dr. David Shoemaker has more than 25 years of experience in research and pharmaceutical development.  He has served as a Program Leader or Advisor for multi-disciplinary program teams and has been involved with products at all stages of the development process. Dr. Shoemaker has managed the regulatory strategy for programs involving multiple therapeutic areas, including hematology, oncology, cardiology, pulmonology, infectious diseases, genetic enzyme deficiencies, antitoxins, and anti-bioterrorism agents.  He has extensive experience in the preparation and filing of all types of regulatory submissions including primary responsibility for four BLAs and three NDAs.  He has managed or contributed to more than two dozen NDAs, BLAs, and MAAs.  Dr. Shoemaker has moderated dozens of regulatory authority meetings for all stages of development.  His primary areas of expertise include clinical study design and regulatory strategy for development of novel drug and biological products.

Karen-1.jpgKaren Kesler, Ph.D.
Assistant Vice President Operations

Dr. Karen Kesler earned both a Master’s and Doctoral degree in Biostatistics from the University of North Carolina at Chapel Hill and has over 20 years of experience in the industry.  Dr. Kesler currently serves as the Primary Investigator of the Statistics and Data Management Center for a NIH sponsored coordinating center researching asthma, allergies, autoimmune disorders, and solid organ transplant.  Dr. Kesler is deeply involved in researching more efficient Phase II and III trials and has led many adaptive studies including sample size recalculations, pruning designs, Bayesian dose escalation studies, and adaptive randomizations.  She has given numerous professional presentations and has over 25 publications and manuscripts to her credit.

Q&A: Using ePRO with Smart Devices

Posted by Brook White on Fri, Jul 17, 2015 @ 10:58 AM
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Emily Cantrell, Senior Director OperationsBecky Baggett, Senior Project ManagerEmily Cantrell, Senior Director Operations, and Becky Baggett, Senior Project Manager recently completed enrollment six weeks early on a phase 3 study using ePRO with a tablet.

On June 10th, we hosted a webinar featuring a case study using ePRO with a smart device. If you missed the webinar, you can click here to register and view the webinar on-demand.

Several questions came up during the webinar that we did not have time to address. Below, we’ve responded to the unanswered questions that were submitted during the webinar.

Q: You mentioned that the guidance on Equivalence Validation is vague and your decision to include was a conservative approach due to the trial being a Phase III pivotal. Can you provide additional comment on when EV will and will not be required?

A: It is difficult to say when this equivalence validation should or should not be performed; however, the impact of the data collected for your marketing claims may help you decide. In our case, since our primary efficacy endpoint for our pivotal phase III was captured on the tablet, the Sponsor and Rho felt it was an important step in support of the data validity. At the time this was a very expensive decision, but it may be the case that the vendor has PROs in their library that have previously been validated, perhaps reducing the impact of cost on your decision.

Q: Are you aware of any tablets that utilize thumb print technology in lieu of a subject PIN?

A: We did not use this technology for our study nor have we been presented with this technology from our vendors.

Q: Can you comment on smart phone apps and other methods for patients to do ePRO at home?

A: Rho does have experience working with a vendor that issues smart phones as at-home devices. The challenges here are ensuring the subjects keep the batteries charged, take care of the device and remember to enter their outcomes. To date, Rho does not have experience using a smart phone application, but we are exploring this option. We have learned that many of the challenges one would experience with the average smart phone technology may complicate the use in clinical trials as well. For example, subjects may inadvertently delete the app from their phone, operation system upgrades may change the way the app interacts with the user, or subjects may lose or damage their phone. One other point of consideration is how subjects may be compensated for the use of their data plan.

Q: Does validation have to be specific to the exact device such as an iPad vs a smart phone app vs another tablet type?

A: In our case, we utilized the exact device with the validation subjects to ensure they were reviewing exactly what the study subjects would be using. For studies that have VAS outcomes, Rho would strongly recommend using the exact device to ensure that the size and scaling did not impact the outcome. For NRS or simple questionnaires, it’s not as pressing, but Rho would recommend obtaining the vendor's prior experience interacting with the FDA to inform the decision.

Q: Do you have experience using an app vs a separate device?

A: To date, we have not yet had experience with using an app versus a device. We realize there may be challenges for this and would want to carefully weigh the options with the Sponsor and study team during study start-up.

Q: How is the translation vendor selected? Does Rho typically select the translation vendor, or do you leave that up to the sponsor or ePRO vendor?

A: Rho has preferred providers for translation, and we do a cost comparison for each bid. There are times where the vendor has been selected by the Sponsor, so we will use their vendor.

Free Webinar: Selecting Inclusion/Exclusion Criteria for Your Next Trial

Addressing Diversity in Clinical Trials

Posted by Brook White on Mon, Nov 24, 2014 @ 09:55 AM
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Shann Williams, Clinical Trials in Transplantation Project DirectorShann Williams is the Project Director of the statistical and clinical coordinating center for the Clinical Trials in Transplantation (CTOT) program sponsored by the National Institute of Allergy and Infectious Disease (NIAID).  In addition, Shann serves as Rho's project management operational service leader, an internal expert overseeing project management processes and training.

Michelle Walter, AVP OperationsMichelle Walter, AVP Operations, has considerable experience directing federally-funded respiratory and allergy clinical research. Her background as a project director of multi-protocol, multi-site clinical programs has been a considerable asset over the course of her fifteen year tenure at Rho.  For the last 8 years, she has been the project director for the Statistical and Clinical Coordinating Center for the Inner City Asthma Consortium, an NIAID-funded network of clinical and mechanistic sites. 

diverse patient/subject populations in clinical trialsA recently released Food and Drug Administration (FDA) report encourages enrollment of more women and minorities in clinical trials. The report identifies three priorities in order to address this need: participation, data quality, and transparency. Clinical research organizations (CROs) can help guide sponsors in all of these areas in order to ensure that their drug and device applications not only meet all of the current requirements, but that they are at the forefront of the direction of the FDA and of biomedical research as a whole.

Overcoming Barriers to Participation:

Finding solutions to barriers that limit participation in clinical trials by demographic subpopulations, particularly those populations that are underserved and underrepresented, is key to diversifying enrollment.

There are several ways sponsors and sites can overcome these barriers. Using available census data, mapping technologies, and peer-reviewed publications to understand the demographic variability of the disease population by region, site-specific enrollment goals and strategies can be created to ensure that percentages of subjects targeted and enrolled accurately reflect the available subpopulation at that site. Similarly, selecting new sites whose community make-up will help achieve enrollment goals can help if other sites encounter limitations.

hurdles to participation in clinical trialsAddressing the needs of non-native English speakers in the United States is immensely important to encouraging diversity. Sponsors can develop appropriate recruitment materials using the subpopulation’s native language and ensure these materials are accessible to the population of interest. Translation services and on-site translators also aid in ensuring informed consent forms are easily understood and thoroughly explained. Choosing translators with the same demographic background as subjects under study helps dispel mistrust and miscommunication. It is also important to administer informed consent forms in a format that is acceptable in that subpopulation. For example, providing adequate time and resources for all applicable family members to review information and offer guidance to the participant about whether or not they should consent may increase enrollment and help reduce drop out during the trial.

Identifying and addressing the motivations, cultural preferences and common barriers to participation for various sub-populations may increase recruitment and retention. Providing solutions to sites to address these barriers – including: tools and training for literacy problems, transportation or reimbursement for transportation, childcare options, flexible visit schedules to help with variable work schedules and options other than checks for participation reimbursements – all help to improve recruitment and retention and diversify enrollment.

Ensuring Data Quality:

As noted in the FDA report, data standards are integral to improving the completeness and quality of information based on demographic subgroups. Identify a CRO partner that has demonstrated leadership in the development and application of data standards. For example, it is important to have subject matter experts that have worked closely with the FDA and its reviewers on numerous clinical development programs, with a track record of successful submissions of several marketing applications with extensive demographic subgroup analyses.

Free Webinar on Cost Effective Data Standards 

 

 

Transparency in Reporting:

transparency in clinical trialsData transparency must be a seamless next step in the clinical trials process, both for submitting reports to the FDA and for informing trial participants of the outcomes. Although the FDA report specifically focuses on data transparency in reporting to the FDA and other data sharing venues, providing study results directly to the trial subjects and their families helps to reinforce that these subjects have personally contributed to research in the disease area that impacts them personally. Results can be presented in the form of newsletters, handouts and tailored materials specific to the subpopulation of interest. This type of transparency further strengthens positive feelings regarding biomedical research as a whole to combat cultural and historical mistrust.

 

Q&A: Clinical Trial Inclusion & Exclusion Criteria Webinar

Posted by Brook White on Fri, Sep 12, 2014 @ 11:27 AM
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questions about inclusion and exclusion criteriaOn September 9th, we hosted a webinar featuring Senior Medical Officer Jack Modell about improving inclusion and exclusion criteria for your next clinical trial.  If you missed the webinar, you can click here to register and view the webinar on-demand.

Several questions came up during the webinar that Dr. Modell did not have time to address.  Additionally, during one part of the webinar participants were asked to submit possible inclusion and exclusion criteria that could be used for a particular scenario, and there were a couple of submitted criteria he did not have time to discuss.  Below, Dr. Modell has responded to the unanswered questions and provided some insight on additional inclusion and exclusion criteria that were submitted during the webinar.

Q: How can you extrapolate your intended patient population between different phases of the trials?

A: Generally, as drug development progresses and more safety information is available, the population can be expanded accordingly.  Thus, phase I trials are usually limited to healthy controls, pivotal trials are generally in a broad target population for whom the drug will be indicated, and phase 4 (post-marketing) trials often extend to previously untested populations (e.g., patients with comorbidities, other target diseases, etc.), safety permitting.

Q: What about adaptive trials, with a number of target groups?

A:Adaptive trials are fine as long as they are appropriately designed with adequate power to detect effects of interest in each group (and the exisiting safety data base makes use in the different groups acceptable).  Cautious use beyond known safety is often appropriate (otherwise we couldn't test or progress new drugs at all); but as always, the potential risks vs. benefits for the research subjects and intended patient populations must be carefully assessed.

Q:Once a patient is in the study, and it is determined that the patient was entered in to the study despite not meeting one of the I / E criteria, do you immediately terminate the patient from the study if it is not a safety issue?

A: Yes, I would generally terminate because you are then studying a subject for whom the study wasn't approved and/or the drug wasn't intended.  These subjects should, however, generally be followed as long as necessary (usually as specified by the protocol) for safety assessments.  Of course, one might counter, "Well, what if the I/E criterion that the subject failed to meet wasn't really that consequential -- 'no big deal, really'?"  To that I would have to ask why an "inconsequential" I/E criterion was included in the first place (maybe shouldn't have been?), but of course that's academic at this point.  Nonetheless, I/E criterion really shouldn't be "second guessed" for subjects once the trial is underway (barring global reassessments and protocol amendments to deal with that), so I would still say that the subject should be discontinued from the study except for safety follow up.  

Q: Is it ethical for the PI to be a participant in the study?

A: Great question.  I'm not sure that it is necessarily "unethical," but the question is whether there's a good reason for the PI not to be a subject.  And for most studies, I think it would be inadvisable because the PI has a vested interest in the outcome and so it would be very difficult for him or her to be completely objective. He or she is hardly representative of the "random" populations that we usually need for drug development.  On the other hand, there may be circumstances, such as when risks are minimal and there is no way that the data can be affected by the PI's vested interest (e.g., a study of height, weight, or other information that is fixed and objective) where the PI's participation might be acceptable.  In any case, if the study is subject to IRB approval, as most are, the PI's involvement should be cleared with the IRB ahead of time.

Q: Many people - not only in EU - consume low to moderate levels of alcohol even during times when they are undergoing treatment. People with blood alcohol should not be excluded because it is reflective of the actual real world population. Any comment?

A: A good point.  But please note that I didn't suggest excluding any alcohol use at all, but rather, only those who could not commit to abstaining for 8 hours before screening and/or randomization (generally not too much to ask considering these 8 hours would usually be in the morning) and those whose BACs are above .015 when tested because this either means that they didn't abstain when they said they would (which raises a question of compliance) or that they had levels 8 hours previous that could only have been attained by very heavy drinking.  One of course could quibble with the ".015" (why not .010 or .020?), but the goal is to do your best to exclude those likely to be heavy drinkers, realizing that you'll lose a few who aren't, but this is generally better than over-including those who do have a problem.  As for the point of testing a drug in the "real world" population of heavy drinkers, if this is really the goal, a separate study (adequately powered and with appropriate precautions) would be a better way to do this.

Exlusion Criteria: Excessive user of depressant drugs such as alcohol - no more than 1 drink a day

Yes, this would be an appropriate exclusion criterion, although would need to be more specific about use of depressant drugs.  One drink a day is reasonable, especially since many subjects will underreport drinking.  

Exclusion Criteria: No history of pre-syncope / syncope. Normal potassium / magnesium. QTcF < 450 msec

Reasonable given that there may be a QTc concern.  

If you have additional questions about the webinar, please submit them in the comments below.  Also, feel free to share additional inclusion/exclusion criteria based on the scenario shared in the webinar.

About the Speaker:

Dr. Jack Modell, Rho Senior Medical OfficerJack Modell, M.D.
Senior Medical Officer 
Dr. Modell is a board-certified psychiatrist with 30 years of experience in clinical research, teaching, and patient care including 10 years of experience in clinical drug development (phases 2 through 4), medical affairs, successful NDA filings, medical governance, drug safety, compliance, and management in the pharmaceutical industry. His specialties and expertise include neuroscience, psychopharmacology, drug development, clinical research, medical governance, and clinical diagnosis and treatment. 

Dr. Modell has authored over 50 peer-reviewed publications in addiction medicine, anesthesiology, psychiatry, neurology, and nuclear medicine. He has lead several successful development programs in the neurosciences. Dr. Modell is a key opinion leader in the neurosciences, has served on numerous advisory and editorial boards, and is nationally known for leading the first successful development of preventative pharmacotherapy for the depressive episodes of seasonal affective disorder.

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Alzheimer’s Disease: Never Too Early

Posted by Brook White on Fri, Nov 01, 2013 @ 11:22 AM
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Clinical Trials and Alzheimer's DiseaseNovember is National Alzheimer’s Disease Awareness Month and National Caregiver Month.

In the United States, Alzheimer's disease is the sixth leading cause of death, and currently, more than 5 million Americans are living with the disease. 


As people are living longer across the U.S., doctors unfortunately are diagnosing more and more people with this slowly progressing, memory-robbing disease. A few well-known sufferers of Alzheimer’s such as President Ronald Reagan, singer Glenn Campbell, and esteemed women’s college basketball coach Pat Summit have helped raise public awareness for the disease over the last several decades. Coming out publicly about their illness has led to an increased effort towards finding a cure for the millions of people faced with a similar fate.


Sadly, 19 years since President Reagan shared his own diagnosis with his fellow Americans, there is still no cure for the disease.


A Sign of Hope


Over the last few years, the medical research community has realized that a new paradigm is emerging for the development of new treatments for Alzheimer’s disease. Although early intervention sounds like a very good idea for any disease, this is not easy when “early intervention” may mean treating people many years before they have recognizable symptoms of the disease. However, in an attempt to develop new treatments for Alzheimer’s, this is what researchers intend to do.


Alzheimer’s disease develops when plaques, which are microscopic clumps of protein deposits, accumulate in the brain. They consist primarily of β-amyloid peptide aggregates and have been recognized for years as a key feature of Alzheimer's disease. This has allowed for the development of a number of drugs that inhibit several of the biochemical processes that lead to amyloid formation and deposition. While some treatments have made it into clinical trials, the results have been disappointing. Several potential treatments have made it all the way to phase 3 studies, only to fail in the demonstration of efficacy.


Many have speculated that these treatments failed because they were tested too late in the disease process. It takes years, if not decades, for amyloid deposition to occur. Currently, researchers use the detection of memory deficits by interviews and cognitive testing to diagnose Alzheimer’s disease. The disease process may have advanced beyond the point where our current drugs can alter the disease course sufficiently to create a signal in a clinical trial if we wait until the symptoms of memory loss are clinically detectible. If potential treatments were tested at earlier stages of the disease, we might be able to see efficacy demonstrated; however, we don’t have a method for accurately identifying patients before they show measurable symptoms.


Academia, regulators, and industry professionals are now working on several major initiatives to change how treatments for Alzheimer’s disease are developed and tested. FDA has recently given industry guidance for designing and executing clinical trials involving patients who do not present with dementia.


Some researchers are considering the FDA’s accelerated approval mechanism in trials where patients present even earlier clinical stages of Alzheimer’s on the basis of cognitive assessments alone. Drugs that address an unmet medical need may be approved on the basis of a surrogate end point or an intermediate clinical end point (e.g., a sensitive cognitive measure) using the accelerated approval mechanism. This regulatory strategy is especially promising for treatments that appear to be effective in early Alzheimer's disease, when patients might be expected to derive the greatest benefit.


To help with this new approach, The National Institutes of Health (NIH) recently announced approximately $45 million in new funding to support research initiatives that will test drugs aimed at Alzheimer’s prevention and identify novel biological targets.

The continued attention, research initiatives, and new funding dedicated to Alzheimer’s research holds promise for developing effective treatments and finding a cure in our lifetime.

Information for this article was contributed by Rho Medical Director Herbert Harris.

 

“What Non-statisticians Need to Know about Statistics in Clinical Trials” Follow Up

Posted by Brook White on Tue, May 14, 2013 @ 10:41 AM
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statistics in clinical trialsWe recently conducted a webinar “What Non-statisticians Need to Know about Statistics in Clinical Trials” featuring Rho Senior Biostatistician Erika Menius. In case you missed it, click here to register and watch the webinar on demand. We wanted to provide answers to some of the questions received during the webinar which we did not have time for during the Q&A session.  We thought a number of these answers would be of interest to a larger group.

Is unblinded the same thing as open label?

Yes, open label and unblinded are considered synonymous.

What parameters should be considered when selecting single blind/double blind/triple blind?

Objectivity of the outcome measure is a primary consideration in determining whether and how to blind your study. If there is any subjectivity in the outcome, the person making the assessment should be blinded and the level of that person determines the level of blinding.

How does FDA view efficacy analysis using Intended to Treat (ITT) versus per protocol populations? Do they look down on one versus the other?

FDA prefers ITT, especially in phase III because it is more generalizable and can help limit bias.

What is the importance of power in analyzing results?

Power uses hypothetical results to make study design decisions (e.g. sample size), so it is only truly relevant during study planning. At the end of the study you are analyzing the actual results, and Power is not a relevant factor in the analysis. However, in a failed study, you can use it to describe whether you had enough patients to see a specific treatment difference.

Describe Type I and Type II error in lay terms.

Type I error: The results indicate that a treatment works when it doesn’t.
Type II error: The results indicate that a treatment doesn’t work when it does.

Can you look at the primary efficacy end point without an interim analysis planned in the study protocol while the study is still on-going?

This is not recommended because it can affect your control of Type I error. If it is not an adequate and well controlled trial you plan to use for a marketing application, it is of less concern, but you should make adjustments as if you planned an interim analysis. FDA is extremely skeptical of doing this during any Phase III trial.

Can you explain allowable error (α), power, and standard deviation?

Allowable error (α) is the same as Type I error. It is the probability that the results will say a treatment works when it doesn’t.

Power is the quantified probability of seeing your treatment work in a given study assuming it does work.

Standard deviation is a common measure of the variability of your data.

What is permuted block randomization?

Permuted block randomization helps ensure a balanced number of subjects across treatment arms by guaranteeing that within a small number of subjects, all treatment arms are covered equally.

What is hot deck imputation?

Hot deck imputation typically is not used in clinical trials. This is a form of imputation where each missing value is replaced with an observed value from a “similar subject.”

Can you use an interim analysis to look at accumulation of cases before you proceed to the next step?

When people say “interim analysis” they typically mean an unblinded look at your data. If you aren’t unblinding, you can look at your data at any time. If you are unblinding, you should have a plan in place and adjust your Type I error accordingly.

Can you explain futility analysis? Can these be done unplanned?

Futility analyses are done to quantify the probability that your study will be successful when your interim results don’t look good. Yes, these can be done unplanned, but you will need to reduce your Type I error (α) for the final analysis.

What is CV?

CV is the coefficient of variation. It is the standard deviation divided by the mean.

Can you explain stratified randomization?

Stratified randomization is used when you want to ensure a balanced number of subjects within a specific factor, such as gender. Subjects are randomized within the stratum.

Do you use Bayesian analysis in clinical trials?

Yes. In clinical trials, Bayesian analyses are most often used in dose escalation studies (e.g., continual assessment method).

What is z(1-α) (from the sample size calculation)?

This is the value of a standardized normal curve associated with 1-α probability (also known as a critical value).

What is the benefit of stratification?

In small studies (typically phase II), stratification reduces the effect of factors that can impact your outcome, making measuring your treatment difference less subject to confounding.

What are the implications of the p-value?

The p-value is the probability that positive results are seen at the conclusion of a study when the drug actually doesn’t work. This value will be small for a drug that truly works.

Why does the p-value change when you do an interim analysis?

When you look at your data more than once, you are more likely to see something you want to see, so you must account for that in your final conclusion by adjusting your p-value.

Is there an equation for how much an interim analysis would affect your Type I error?

Yes, there are a number of equations you could use, such as an α spending equation.

How does FDA see ad hoc analysis used in submission?

An ad hoc analysis can help support the primary analysis or help explain safety issues or biologic mechanisms, but it is unlikely FDA would grant approval based on an ad hoc analysis alone.

Can you review how hazard ratios impact size and length of a trial?
More extreme hazard ratios (either larger or smaller than 1) are associated with the need for smaller and shorter studies. Note: This is a general answer to a highly complex topic.

Is a different sample size calculation equation needed for small clinical trials, large clinical trials, or both?

The sample size calculation is always relevant, no matter the size of the trial. It quantifies how much of a treatment effect you can expect to believe for your study size.

What is incomplete block study design?

This is a study design where you have blocks of subjects and multiple treatments, but not all treatments are appropriate for all blocks. For example, you might have three blocks—pediatric, adult, and geriatric—and two treatments (A and B) where the first treatment (A) isn’t appropriate for pediatric patients and treatment B isn’t appropriate for geriatric patients. In that case, you would have a block of pediatric patients on treatment B, a block of adult patients on treatment A, a block of adult patients on treatment B, and a block of geriatric patients on treatment A.

How is the calculation of n affected when comparing a diagnostic to a gold standard?

If your gold standard is not variable (or only slightly variable), it can reduce your sample size. It can also affect your study design because you may be doing an equivalence study instead of a superiority study. Note: This is a brief answer to a complex question.

Do you have a question from the webinar that isn't answered here?  Submit it through the comments.

View Adaptive Design 101 Video

 

Conducting CNS Clinical Trials? Overview and Considerations of the New Tools from NIH for Assessment of Neurological and Behavioral Function

Posted by Brook White on Tue, Apr 16, 2013 @ 09:29 AM
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neuropsychological assessments in clinical trialsIn recent years the National Institutes of Health (NIH) has undertaken several initiatives intended to advance neuroscience research by means of a multi-institute collaboration entitled “the Blueprint for Neuroscience Research.” Some of these initiatives involve standardization and sharing of cutting-edge technologies such as neuroimaging and genomics. Another of their initiatives, the NIH Toolbox, is a set of standardized neurobehavioral assessments that is useful to a broad research audience.   This article summarizes the development-of and uses-for the NIH Toolbox, and provides considerations for its current and future utility in drug development1.

Many central nervous system (CNS) clinical trials, as well as those in other therapeutic areas, require neurological or behavioral assessments.  Currently, investigators use a number of different assessments to assess the same construct, making it difficult to understand data across multiple studies.  In an effort to resolve this problem in 2004, the NIH formed a coalition to create a toolbox of neurological and behavioral assessments.  The coalition included multiple divisions at NIH and more than 250 scientists at more than 80 institutions.  The goals of the coalition were:

  • To develop and validate a set of standardized, psychometrically sound tools for neurobehavioral constructs
  • To be able to measure the same construct across the life span
  • To create tools that are royalty-free, and as close to cost-free as possible (most assessments currently in use are proprietary and often costly)
  • To create tools that are efficient to administerTo provide measures that facilitate the pooling of data across many studies

In October of 2012, the coalition released the toolbox to the public.  It includes:

  • Four domain level batteries
  • English and Spanish versions
  • 34 supplemental instruments
  • Training materials for administration of the assessments
  • Public data from the studies conducted during the development of the tools

The batteries are fully normalized for ages 3-85, and are essentially free to use.  Each domain takes 30 minutes to administer.  From the toolbox website, you can access the domain level batteries, supplemental assessments, and training materials including videos showing the assessments being conducted.

The four domains covered by the assessments are cognition, motor, sensation, and emotion. The cognitive domain includes working memory (short term buffer), executive function (planning and organizing), episodic memory (acquisition and retrieval), language, processing speed, and attention.  The motor domain includes standing balance, strength, dexterity, and speed/endurance.  The sensation domain includes audition, olfaction, pain, taste, vestibular, and vision.  The emotional domain includes psychological well-being, social relationships, stress and self-efficacy, and negative affect.

What will be the impact of the NIH toolbox on CNS clinical trials and the development of new treatments for CNS disorders?  They are not designed to capture pathology, and so far, they have been used primarily in health subjects. Therefore, the NIH Toolbox is unlike earlier initiatives such as the ECDEU assessment manual for psychopharmacology published in 1976, which had a profound effect on drug development through the late 1980s.  However, because of its focus on function in healthy subjects, the NIH Toolbox may provide a more precise and quantitative concept of “normal” against which pathology can be measured. As such, it will inevitably have utility throughout clinical research and drug development. 

It may take some time to gain broad acceptance in the CNS community.  For now, it seems risky to use one of these assessments alone as a primary end point for a clinical trial, and if you are considering doing so, you should probably proactively pursue agreement from the FDA. Another consideration is how you would use the assessments in a trial.  Most of the assessments are aimed at benchmarking a state of wellness.  While that doesn’t provide a direct measurement of disease state, these tests may be valuable in showing clinical significance.  

Have you used or considered using any of these assessments yet?  If so, share your experiences in the comments section.

For more information, see the NIH Toolbox website www.nihtoolbox.org where the assessments and training videos can be found.

1Information for this article was contributed by Nancy Yovetich, Ph.D., Senior Research Scientist, and Herbert Harris, M.D., Ph.D., Medical Director at Rho, Inc.  These contributors were not involved in the development or validation of the NIH Toolbox.  One of the authors did attend the launch of the NIH Toolbox in Bethesda, MD.  Both Dr. Yovetich and Dr. Harris have extensive backgrounds in clinical research and in psychology/psychiatry.

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