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Could Your Drug Development Program Benefit from an NDA/BLA/PMA Gap Analysis?

Posted by Brook White on Wed, Aug 23, 2017 @ 09:37 AM
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David Shoemaker, PhD--Senior Vice President R&DDavid Shoemaker, PhD, Senior Vice President R&D, 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 and has moderated dozens of regulatory authority meetings.  

Jack Modell, MD--Vice President and Senior Medical OfficerJack Modell, MD, Vice President and Senior Medical Officer, 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) and successful NDA filings. Dr. Modell is a key opinion leader nationally known for leading the first successful development of preventative pharmacotherapy for the depressive episodes of seasonal affective disorder.

scott-burian.jpgScott Burian, PhD, Senior Research Scientist, has contributed to the development of a diverse range of small molecule, biologic, and nanoparticle-based products.  He has participated in numerous FDA interactions, including pre-IND meetings, Type A meetings, and Advisory Committee meetings. He is fully-versed in eCTD format and has authored a variety of CMC submissions, including numerous pre-IND meeting packages, INDs, NDAs, and IMPDs.

bridging the gap between clinical data and NDA submissionHere at Rho, we’ve helped many companies with their marketing application submissions. In fact, in the past six years, we’ve been a key service provider on 14 submissions, provided biostatistics support for 30 submissions, and prepared over 20 Integrated Summary of Safety (ISS) and Integrated Summary of Efficacy (ISE) SAPs. Over the course of working on these submissions, one common hurdle we see is that Sponsor companies often enter this stage without a strong understanding of what data they have and how that maps to a viable approval pathway.

Whether you plan to file a new drug application (NDA), a biologics license application (BLA), or a premarket approval application (PMA) with the FDA or a marketing authorization application (MAA) with the European Medicines Agency, you’ll need an in depth understanding of how the data you have from your clinical studies, nonclinical studies, and Chemistry, Manufacturing and Controls (CMC) / Quality development map to the requirements of the application. These requirements can be specific to the therapeutic area or regulatory authority, and are continually changing as science advances.

Discovering you don’t have all the data you need as you begin preparing your marketing application can lead to costly time delays. What can be done? We recommend undertaking a gap analysis following proof-of-concept in Phase II. This timing allows you to design your adequate and well-controlled studies to attain all necessary clinical data. Performing the gap analysis at this stage of development will also provide enough time to conduct additional nonclinical studies or CMC development that may be needed to support the application.
You need a cross-functional team of medical, regulatory, clinical, statistical, CMC, and toxicology experts with experience getting a product to market, ideally in the therapeutic area of interest. Many small to mid-size companies don’t have all of this expertise in-house, so the team will need to bring in outside support in the form of consultants or a contract research organization (CRO) that has this expertise.

A gap analysis starts with a detailed look at the existing data and regulatory communications. What is the format of the data? Anything you plan to submit will need to be in CDISC format, so if you need data from legacy studies, the data must be converted to CDISC format if the study was initiated after December 2016. Next, look at the label claims you plan to make. Do you have (or have a plan to collect) all the data needed to support those claims? This can be difficult to determine.

mapping clinical dataOnce you’ve determined the data you have and the data you’ll need, create a map that clearly identifies the deficiencies in your database. You may find that there are very few gaps and the data you’ve collected and will collect in your pivotal studies will adequately support your marketing application. You may also realize that you don’t need all of the data from your legacy studies, which can save you some time and money in CDISC conversion costs. Conversely, you may identify significant gaps in your database that require additional studies. That is still a good outcome because by performing the gap analysis you have clearly identified what needs to be completed and you will have sufficient time to gather the additional data. This could mean just completing your Phase 3 studies, or performing additional clinical (e.g. food effect studies) or nonclinical studies, or CMC development work, thus ensuring that upon completion of the Phase III studies, you will have a clear path to your marketing application submission.

So, is the additional time and expense of conducting a gap analysis worth it? Rho believes that the answer is most definitely, yes. However, we typically recommend waiting until proof-of concept has been demonstrated to conduct this analysis. At that point, you should have convinced yourself that you have a viable product and have a general idea of its characteristics and potential value to patients. An experienced team of medical, nonclinical, CMC, regulatory, and statistical experts can conduct a gap analysis relatively quickly and for a relatively limited cost. When compared to a significant delay between the end of Phase 3 and submission or an unsuccessful marketing application submission, it is almost certainly worth it.

Download: Marketing Application Planning Tool

Key Take-aways from ACRP 2017

Posted by Brook White on Fri, May 05, 2017 @ 11:15 AM
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key take aways from ACRPThis week I attended the 2017 ACRP Annual Meeting in Seattle.  Here are some of the key trends, themes, and ideas that I took away.  There were obviously far more sessions than any one person could attend, so I’m sure there are pieces I missed.  If you attended, please feel free to add your thoughts to the comments below.

Core Competency Framework for Clinical Study Monitoring

framework for clinical study monitoringOne of the biggest announcements of the conference was that the Workforce Development Task Force and Steering Committee released a core competency framework for clinical study monitoring.  The goal of the framework is to standardize professional expectations for individuals involved in clinical study monitoring.  The framework is intended to define competency requirements for individuals involved in study monitoring regardless of experience level across eight domains—clinical operations/GCPs, communication and teamwork, data management and informatics, ethical and participant safety concerns, leadership and professionalism, medicines development and regulation, scientific concepts and research design, and study and site management. The core competency framework can be downloaded here.

ACRP Announces New Certification Program

certified professionalACRP announced a new certification program, ACRP-CP (certified professional).  The new certification provides a non-role specific alternative to the existing role specific Certified Clinical Research Associate (CCRA), Certified Clinical Research Coordinator (CCRC), and Certified Principal Investigator (CPI) certifications.  The new credential seeks to formally recognize individuals with the skills, knowledge, and abilities to perform ethical and responsible clinical research regardless of their specific role.  The first certification exam will be held this Fall.

Transparency and Flexibility from FDA

regulatory transparencyThe first session on Saturday was a panel discussion with four speakers from FDA—three from the Center of Drug Evaluation and Research (CDER) Office of Scientific Investigations (OSI), and one from CDER Office of Integrity and Surveillance. As I commented following ACRP and DIA last year, FDA seems to be making a concerted effort to be accessible, transparent, and flexible in communicating with professionals involved in research. As a matter of fact, one of their stated strategic goals was stakeholder engagement (the others were user fee requirements, responsible stewardship, global context, and subject rights, safety, and welfare). They also stated that in places where existing guidance and precedence doesn’t exist and is needed to move research forward, drug developers should come to them with questions rather than waiting for formal guidance. In addition to the panel discussion, the three speakers who attended in person stuck around and held office hours Saturday and Sunday to talk to conference participants.

The panel addressed several questions that related to themes seen more broadly at the conference.

State of the Industry

Day 2 opened with a panel discussion on the state of the industry featuring ACRP President Jim Kremidas, Ken Getz from Tufts University Center for the Study of Drug Development (CSDD), Elisa Cascade, President of Data Solutions, Leanne Madre Director of Strategy for the Clinical Trials Transformation Initiative (CTTI) at Duke University, and ACRP’s Workforce Innovation Officer, Terri Hinkley.  The panel focused their discussion on four broad forces impacting clinical trials:

  • Consolidation
  • Datafication
  • Integration
  • Uberization

Organizations involved in clinical trials are consolidating across the continuum. We are seeing both consolidation for economies of scale—CRO mergers and acquisitions, sites fusing into site networks—and vertical consolidation where organizations are increasing their capabilities—CROs buying site networks and central labs. It remains to be seen how this will impact clinical trials as a whole.

Datafication is the increased ability to gather and access ever increasing amounts of both structured and unstructured data that can be used in clinical research. The average phase III study now collected nearly 1 million data points. Additionally, we are seeing more data that is collected to drive payer and prescriber behavior rather than just to demonstrate safety and efficacy.

Integration refers to the efforts to better connect people, processes and technology. There are a number of national level initiatives to improve clinical research like CTTI, TransCelerate, and MDIC, a device and diagnostic initiative. These organizations have potential to move some agreed upon concepts from idea to reality. For example, both the NIH and the 21st Century Cures Act call for use of central IRBs, and CTTI is working on tools that can help make that happen. When it comes to technology, the perception is that the industry is suffering from “death by pilot.” People and organizations are willing to try lots of new technology, but consistent industry wide adoption is incredibly slow and lacking in standardization. Even EDC, which is hardly new or innovative at this point, is only used by 50% of studies globally. Common complaints and barriers include lack of consolidated platforms and the need to use different software and different login information for each study.

Uberization is moving research into healthcare in a way that works best for patients. There are greater pressures than ever to make research patient friendly rather than convenient for sites, PIs, CROs, and sponsors. Without patients, studies won’t happen. In this talk as well as others, there is a sense that patient centric practices aren’t just the right thing to do, they are necessary to succeed in research.

Finally, the panel identified key drivers for change over the next 3-5 years:

  • Collaboration: Industry and CROs working together allow for standardization and process improvement.
  • Regulatory willingness to try new things.
  • The internet of things—devices in our lives provide access to information in new and objective ways.
  • Technology that is easy enough to use that training isn’t necessary.

Innovating Clinical Trials with Mobile Technology

mobile technology for clinical trialsDay 3 featured a panel discussion on the CTTI mobile technology initiative.  The initiative contains four working groups addressing:

  • Mobile devices
  • Novel endpoints
  • Stakeholder perceptions
  • Legal and regulatory issues

The goal is to provide evidence-based recommendations that allow an increased number of clinical trials to leverage mobile technologies.

One question they addressed upfront was the benefit of using mobile given the additional effort needed, and they provided four key answers:

  • Potential reduction of burden on trial participants
  • Increased patient access to clinical trials
  • Availability of objective data
  • Ubiquity of devices

The initiative has focused on studies conducted in the US, although they recognize it is a global issue. The stakeholder perception group is addressing concerns about security as well as concerns about losing the time and attention of the doctor providing care. The novel endpoints group is looking at new endpoints that are now possible to assess as well as existing endpoints that can be assessed more easily or more accurately than is possible with non-mobile technologies. The mobile devices group is looking at devices that can address existing challenges, data attribution concerns, and the identification of the difference between real needs to address research questions versus data fishing expeditions. The legal and regulatory group has its hands full with a variety of issues—understanding FDA’s willingness to accept mobile technologies, addressing privacy and confidentiality concerns, telemedicine challenges, dealing with IRBs, shipping issues, and reimbursement.

Finally, people were invited to engage in the process by signing up for updates or to participating in evidence gathering (ctti@mc.duke.edu).

eHRs and Study Oversight

A significant concern expressed by auditors and monitors alike in a number of sessions is that site and institutions implementation of eHR systems do not provide adequate mechanisms for monitors and auditors to provide oversight.  In some cases they are being provided with copies or printouts that are illegible rather than provided with direct access to eHR systems.  In other cases, they are provided with access to eHR systems, but important information is sequestered.  A common complaint is that sensitive records like those associated with mental illness, sexually transmitted infections, and substance abuse is are not being made available even when those records are relevant to the research and may reflect AEs.  In one example, it came to light that a subject had attempted suicide while on an investigational product, but it was not initially reported as an AE and the study monitor was not allowed access to the record.  With the increased use of eHRs in healthcare settings, this is not likely an issue to go away soon.

ICH E6 R2

Not surprisingly, many if not most sessions touched on the impact of the ICH E6 revisions and their impact to studies.  Additionally, there was a two part session held specifically to review the revisions and discuss their impact.  This is an extensive topic that is well discussed elsewhere, so I won’t go into detail here. 

Importance of Conducting Ethical Research

While this isn’t new, ACRP continues to press the importance of conducting clinical research in ethical ways and expecting professionals involved in research to understand what that means.  There were a number of excellent sessions on research misconduct and the relationship to public trust, ethical considerations in pediatric research, and recognizing vulnerable patients and patient populations.

Business Intelligence and Study Management

As the global volume of available data sources increases exponentially, those in clinical research are becoming more aware of the benefits of transforming these raw data sources into useful information for analysis purposes. The ability to effectively utilize the data we currently have depends on the thoughtful construction of metrics and key performance indicators (KPIs). The simple establishment of these types of measures must develop an even balance; a study can have too many metrics (which confuse the purpose), too few metrics (which offer weak benefit and minimal impact), or a focus that is too broad where one area grows strong at the expense of another. Other common pitfalls are underestimations of the time and effort required to combine various data sources, imbalances between metrics and action, and metrics that are developed for the sake of metrics. The development and use of these metrics and KPIs requires a cycle of continuous improvement: High-impact metrics must be identified and developed, accurate data gathered, and the lessons learned converted to actionable strategies and reassessed continually to correctly estimate our return on investment.

Thanks to Derek Lawrence for contributing to this article.

Big Data: The New Bacon

Posted by Brook White on Wed, Nov 16, 2016 @ 04:10 PM
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Dr. David Hall, Senior Research ScientistDavid Hall is a bioinformatician with an expertise in the development of algorithms, software tools, and data systems for the management and analysis of large biological data sets for biotechnology and biomedical research applications. He joined Rho in June, 2014 and is currently overseeing capabilities development in the areas of bioinformatics and big biomedical data. He holds a B.S. in Computer Science from Wake Forest University and a Ph.D. in Genetics with an emphasis in Computational Biology from the University of Georgia.

big data is the new baconData is the new bacon as the saying goes. And Big Data is all the rage as people in the business world realize that you can make a lot of money by finding patterns in data that allow you to target marketing to the most likely buyers. Big Data and a type of artificial intelligence called machine learning are closely connected. Machine learning involves teaching a computer to make predictions by training it to find and exploit patterns in Big Data. Whenever you see a computer make predictions—from predicting how much a home is worth to predicting the best time to buy an airline ticket to predicting which movies you will like—Big Data and machine learning are probably behind it.

However, Big Data and machine learning are nothing new to people in the sciences. We have been collecting big datasets and looking for patterns for decades. Most people in the biomedical sciences consider the Big Data era starting in the early to mid-1990s as various genome sequencing projects ramped up. The human genome project wrapped up in 2003, took more than 10 years, and cost somewhere north of $500 million. And that was to sequence just one genome. A few years later, the 1000 Genome Project started, whose goal was to characterize genetic differences across 1000 diverse individuals so that we can predict who is susceptible to various diseases among other things. This effort was partially successful, but we learned that 1000 genomes is not enough.

cost of human genome sequencingThe cost to sequence a human genome has fallen to around $1,000. So the ambition and scale of big biomedical data has increased proportionately. Researchers in the UK are undertaking a project to sequence the genomes of 100K individuals. In the US, the Precision Medicine Initiative will sequence 1 million individuals. Combining this data with detailed clinical and health data will allow machine learning and other techniques to more accurately predict a wider range of disease susceptibilities and responses to treatments. Private companies are undertaking their own big genomic projects and are even sequencing the “microbiomes” of research participants to see what role good and bad microbes play in health.

Like Moore’s law that predicted the vast increasing in computing power, the amount of biomedical data we can collect is on a similar trajectory. Genomics data combined with electronic medical records combined with data from wearables and mobile apps combined with environmental data will one day shroud each individual in a data cloud. In the not too distant future, maybe medicine will involve feeding a patient’s data cloud to an artificial intelligence that has learned to make diagnoses and recommendations by looking through millions of other personal data clouds. It seems hard to conceive, but this is the trajectory of precision medicine. Technology has a way of sneaking up on us and the pace of change keeps getting faster. Note that the management and analysis of all of this data will be very hard. I’ll cover that in a future post.

View "Visualizing Multivariate Data" Video

Scientists Search for Answers as Antibiotics become Obsolete

Posted by Brook White on Thu, Aug 18, 2016 @ 01:41 PM
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Carrie Furr, PhD, RACCarrie Furr, PhD, RAC, is a Senior Director Operations at Rho. Day-to-day, Carrie supports pharmaceutical sponsors of clinical trials, leading an integrated product development program consisting of clinical, preclinical, chemistry, manufacturing and controls, and regulatory components. Before diving into the clinical trials industry, Carrie spent 7 years earning her PhD in biochemistry, bacteriology and bacteriophage biology at Texas A&M University. A biologist by training, Carrie’s dissertation and doctoral research focused on how a bacteriophage (phage) protein causes bacteria to die. In theory, phage proteins can be used in phage therapy to combat any bacteria-based disease. 

As anyone who has ever had a bacterial infection or seen an end-of-the-world survival movie knows, antibiotics are an important tool in a doctor’s arsenal. Since the discovery of penicillin in 1928, antibiotics have been extremely effective at treating and preventing a variety of infections. But imagine life without them – doctors unable to prevent infections after surgery, your child’s minor cut might morph into a major infection, and there wouldn’t even be a treatment for pink eye.

With the increasingly popular use of antibiotics, however, microbes have mutated and learned to resist the drugs. Penicillin was once extremely effective against most strains of bacteria, but now it is used far less frequently as many strains have built up resistance. In many cases antibiotics are becoming obsolete.

What can be done? Without antibiotics, a huge range of diseases -- from pneumonia to strep throat to syphilis – would become much more difficult, if not impossible, to treat. While there are a few things you can do to help prevent antibiotics from further increasing resistance – for example, taking all prescribed antibiotics even if you feel better or only taking antibiotics when you truly have an infection – it isn’t enough. Scientists need to work on other solutions.

phage, bacteriophageBacteriophages, or “phages” for short, may be able to help. Certain phage proteins cause bacteria to die. Researchers are working to determine if these proteins or whole phages can be safely converted into therapies to combat bacteria-based diseases. Developing an alternative treatment to antibiotics could have huge implications on the treatment of bacterial infections around the world. Additionally, phage therapy holds the promise of providing a dynamic solution to the dynamic problem of antibiotic resistance.

While academics and pharmaceutical companies work on the research, people like me are working on smoothing the road to U.S. Food and Drug Administration (FDA) approval for these novel therapies. As a postdoctoral researcher, I focused on how bacteriophages can kill certain bacteria. As a senior regulatory scientist, I work on the practical steps required to bring pharmaceutical products, including phage therapy, into the market to treat patients. Currently, the path to develop phage therapy through to regulatory approval is unclear.

In the face of antibiotic resistance in the U.S. and around the world, it is important to understand our alternatives and what must be done to advance alternative treatments.

Webinar: Tips for a Smooth NDA Submission

Top Trends in Drug Development from This Year’s DIA Annual Meeting

Posted by Brook White on Tue, Jul 12, 2016 @ 02:41 PM
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During the last week of June, the Drug Information Association held its 52nd Annual Meeting in Philadelphia.  As one of the largest conferences in our industry, DIA covers a wide range of topics over the entire spectrum of drug development, and it would be nearly impossible to provide a comprehensive accounting of the meeting.  However, I will try to share the most notable trends and themes from the meeting.

Big Data

big data in drug developmentBig data was possibly the hottest topic this year.  Not only did FDA Commissioner Dr. Robert Califf participate in a panel session on the topic, but when listing his top four priorities, one of them was greater use of existing data in EMR/EHR systems.  At DIA, people were really talking about big data from a handful of sources—electronic medical records data, data from wearables, data from social and digital media and genomics (and other -omics) data.  FDA is taking a lead role in the use of big data and real world evidence through initiatives like Sentinel, which enhances the FDA’s ability to proactively monitor the safety of medical products on the market, and precisionFDA, a community platform for next generation sequencing (NGS) assay evaluation and regulatory science exploration.  Big Data is an idea that has been talked about for some time, but based on this year’s meeting it is clear we’ve moved beyond idea to reality.  For anyone wondering how soon we might see full genomic sequencing of all patients in a clinical trial, you will be interested to learn that the cost is now on par with a chest x-ray, Genentech has sequenced 30K genomes to date, and AstraZeneca recently entered into a partnership with Human Longevity to sequence 500K genomes over the next 10 years.

Patient Centricity is Still Big

patient-centricityPatient centricity was the theme of last year’s meeting, and continued to play a central role in this year’s meeting.  But while last year was big on ideas and optimism, this year saw early adopters sharing lessons learned from programs already up and running.  Patients and patient advocacy groups made up a noticeable group of attendees and were outspoken during sessions.  Several companies including Bristol Myers Squibb (BMS) and GlaxoSmithKline (GSK) shared specific programs and tactics they’ve been using to move to a more patient focused research model.  Some examples include creating frameworks that allow greater number of employees to engage with patients and the public about the work they are doing and developing minimum standards for patient engagement that reflect geographic and cultural differences.  From a regulatory perspective, patient-centricity made Dr. Califf’s list of his top four priorities.

7 Tips to Use Social and Digital Media to Recruit and Engage with Clinical  Trial Patients

The Swinging Pendulum on Outsourcing

swinging pendulum on outsourcingFor many years now, it seemed the trend was always to more and more outsourcing with innovator companies keeping fewer and fewer activities in house.  Several of this year’s outsourcing sessions are hinting that the pendulum on that trend may be starting to swing back.  From internal frustrations with outsourcing groups, to dissatisfaction with vendors in terms of both quality and performance, to the failure of preferred provider relationships to deliver on expected savings and improvements, the talk from a number of pharmaceutical and biotech companies is that they are keeping more work in-house. That said, there certainly is not agreement among sponsors or vendors/suppliers on this issue.  Many pointed to issues at sponsor companies such as refusal to hear feedback from CROs on the feasibility of their budgets, timelines, or study designs as well and disagreement between outsourcing personnel and study team personnel about the providers being selected.

Drug Development as a Calling

DIA opened with keynote speaker Dr. Larry Brilliant, a physician and epidemiology who participated in the World Health Organization’s (WHO) successful small pox eradication program.  Dr. Brilliant talked through a number of health research and outreach efforts that have dramatically changed the world for the better, including the small pox and polio eradication programs, the development of electrolyte solutions to treat cholera and diarrhea, and more recently the efforts of the Carter Center to eradicate guinea worm.  He brought into sharp focus the idea that what each of us in the pharmaceutical industry does has the potential to change the world for the better.  The idea of drug development as a calling was furthered by Dr. Califf’s call to all of us to donate the information in our electronic health records for the betterment of research and medicine—a reminder that we should be willing to open ourselves up in the same way that we ask patients and research participants to do.  Finally, several of the patient-centricity speakers focused on the value of identifying employees who themselves were patients or care-takers of patients in their private lives in addition to being part of the research and development process.  These people are uniquely qualified to help us better understand the patients’ needs and experiences.

Greater Engagement by FDA

Finally, it was interesting to me to see the level of participation by the FDA in this year’s meeting. While they always send some presenters and a larger number come just to attend, this year did seem different. Dr. Califf presented in multiple sessions and was open and engaging during Q&A sessions. Additionally, numerous sessions included speakers and panelists from the FDA providing valuable insight into their point of view.

Did you attend DIA this year? If so, let me know what you thought.

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.

4 Top Trends in Drug Development: DIA 2015 Recap

Posted by Brook White on Tue, Jun 23, 2015 @ 11:04 AM
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Last week, the Drug Information Association held its 51st Annual Meeting.  As one of the largest conferences in our industry, DIA covers a wide range of topics over the entire spectrum of drug development, and it would be nearly impossible to provide a comprehensive accounting of the meeting.  However, I will try to share the most notable trends and themes from the meeting.

Patient-centricity

patient-centricClearly, one of the biggest take-aways from DIA was patient-centricity. While for many of us patients have long been the motivation for the work we do, patients now are playing a central role throughout the drug development process. In addition to their roles as patients in clinical trials and eventual consumers, patients increasingly are participating in all aspects of development, from study design to advisory committee meetings. As we make this transition, patient advocacy groups can be powerful allies in reaching out to patients.

Some keys to patient outreach and involvement are relevance, logistics, and psycho-social components. For patients to be on-board with trials, they need to understand why a study is relevant. Patients need to see the link between how their participation now can lead to improvements in treatment in the future. Often, patients are interested in the outcomes past their own participation. Keep them updated as trials complete and results are available.

Patients can also provide useful insights on logistics. What may seem like minor considerations to scientists and others involved in study design, could be significant when it comes to patient participation. Logistics around scheduling, childcare, and uncomfortable procedures can be a study’s downfall if patients aren’t willing to sign-up or eventually drop-out because of inconveniences.

There are psycho-social issues that should be considered for certain patient populations and conditions. For example, it is likely that diabetics would have little concern over using an injectable treatment. Many have already used injectable products or have at least considered the need to use them in the future. On the other hand, patients used to oral dosing may have objections.

Finally, one suggestion made by a patient advocacy group at the meeting was to have all members of the clinical study team spend a day with a patient from the population being study. Understanding their daily routines and struggles can provide important insights.

Social Media is Big—And Getting Bigger

social media and drug developmentNearly every track featured at least one presentation on social media. We are now moving past theoretical uses to real world applications in patient recruitment, medical information, safety monitoring, and even regulatory agencies.

Use of social media is becoming commonplace in patient recruitment. In addition to being a more cost effective option when compared to traditional media like broadcast, radio, and newspaper ads, it also allows for better targeting and reporting. For example, social media allows you to show ads only to those within appropriate demographic groups. Even demographic groups previously considered poor targets for social media, like the elderly or lower income populations, are increasingly online in one way or another. Additionally, Sponsors and CROs have largely found ways to address regulatory and privacy concerns.

Medical Information is another area where social media use is increasingly common. With several FDA guidance documents now in place, Medical Information professionals’ perspectives on social media are changing. Patients making contact with pharmaceutical companies are being seen less as a risk to respond to and more as an opportunity to engage proactively. While companies should still be careful to present scientifically-based balanced information, social media can provide an opportunity to correct faulty information and even respond to questions about off-label use in a non-promotional way.

Safety monitoring is another area primed for growth in social media use. With the question of how to deal with adverse event reporting through social media largely handled—be prepared for it and treat it the same way you would treat reports coming in through traditional channels—product safety professionals are turning their attention to ways they can use social media to improve patient safety. Dr. Ran Balicer of the Clalit Research Institute is pioneering a system to identify safety signals in social media and compare it to information being reported by clinicians and to regulators.

Regulatory agencies are embracing social media as well. FDASIA Section 1138 instructs the FDA to create a communication plan to better inform and educate consumers with a focus on communicating with underserved sub-groups. The working group at FDA is relying on social and digital media to build the core of this program.

Outsourcing Trends

Despite incredible growth in outsourcing over the past 20 years, Sponsors still struggle with the right balance of outsourcing models. Both Sponsors and CROs report dissatisfaction with outsourcing relationships. Strategic relationships aren’t delivering the promised cost and time savings. The number of companies entering into strategic alliances and functional service provider relationships has been steadily growing over the past few years, yet virtually all Sponsors admit that they are still making outsourcing decisions (full service, FSP, or niche providers) on a study by study basis.

key performance indicatorsOne major challenge identified by several speakers is the ability to select key performance indicators (KPIs) that both accurately measure the CROs performance and those for which CROs are prepared to provide the data necessary to produce the metric. Existing KPIs have largely been selected because they are easy to measure and report on regularly, but they are often a better measure of the study design and the Sponsor’s ability to manage the relationship than they are a measure of the CROs performance. However, ability to produce metrics and willingness to be transparent continue to be make-or-break for Sponsors when it comes to selecting preferred providers, entering into strategic alliances, and picking functional service providers.

eSource, eTMF, and Risk-Based Monitoring

Perennial favorites, there was no shortage of presentations on the topics of electronic trial master file (eTMF) solutions, eSource and electronic data capture (EDC), and risk-based monitoring. Although eTMF has been a hot topic for a number of years, adoption is still slow. Many companies are considering implementing an eTMF, but most are still using paper systems, network file systems, content management systems, or a combination. However, growing Sponsor expectations for remote access to TMF documents combined with improved audit readiness will continue to push CROs in this direction.

risk-based monitoringOn the other hand, risk-based monitoring has become a reality for many studies. Companies have been investing in tools and processes and regulators continue to show support. As a result, more studies are taking advantage of the benefits of risk-based monitoring.

Although it has seen widespread (and in some instances near complete) adoption, EDC has left many feeling it hasn’t lived up to expectations. It hasn’t reduced significantly the cost or time of trials. Because much of the information clinicians need to record during study visits isn’t recorded in the CRF, information is still being recorded in one place and then transcribed into EDC. eSource—a combination of ePRO tools, EHR/EMR integration with EDC, and other electronic sources—offers new hope to deliver on the original promise of EDC.

Were you there? If so, use the comments to let me know what you thought were the most important take-aways from DIA this year.

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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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Key Tips for Orphan Product Development

Posted by Brook White on Tue, Aug 27, 2013 @ 10:47 AM
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David Shoemaker discusses orphan product developmentInformation for this article was contributed by David Shoemaker, Senior Vice President R&D. Dr.  Shoemaker has over 25 years of experience in research and pharmaceutical development.  He has managed or contributed to dozens of INDs/CTAs and over a dozen successful NDAs, BLAs, and MAAs.  Dr. Shoemaker has authored or overseen dozens of Orphan Drug Designation applications, has developed several successful Accelerated Approval programs, and has secured several Priority Review applications.

Selecting a partner for drug development is tricky.  This is especially true when selecting a CRO to assist with orphan product development.  Finding a partner that has both the experience and expertise needed as well as being a good cultural fit for your company is critical to achieving your goals. 

  1. Work with CROs that have strong scientific, regulatory, and statistical expertise
    A strategic approach with a focus on key milestones is critical to gain approval as quickly as possible. Look for CROs whose strengths include the ability to conduct challenging clinical trials, knowledge of the regulatory process, and scientific and statistical expertise to develop a plan for success at the outset to reach approval in an expedited speedy manner. Your CRO should have successfully obtained marketing approval for other orphan products previously. Marketing applications for orphan products require creative regulatory and statistical strategies to leverage the data obtained on populations much smaller than typically seen by regulators.
  2. Know the “ins and outs” of the U.S. Food and Drug Administration’s approval mechanisms to help speed orphan drug approval
    Many orphan diseases represent serious or life-threatening conditions. Consequently, working with a development partner that understands each of the accelerated development pathways (i.e., Accelerated Approval, Priority Review, Breakthrough Therapy, and Fast Track) and the potential benefits or lack thereof is critical. Making an informed decision on the best mechanism at the start of the orphan drug approval process is the fastest path to approval.
  3. Apply for US and European Orphan Drug Designation Simultaneously
    There is a combined form that can be used to obtain orphan drug status simultaneously in the US and EU. It is an option that is not being used broadly, but can result in significant reduction of time and effort.
  4. Look for a CRO partner with experience working in small patient populations 
    Working with small patient populations requires building communities and developing close connections with research foundations, advocacy groups, patients and health care providers for a purpose-driven approach to product development. It will also be important to gain buy-in from Key Opinion Leaders.
  5. Validate your population
    Before investing time and energy in an orphan drug application, make sure you are eligible. Regulators are on the lookout for developers who try to “slice the salami” meaning that your orphan population is really just a subset of a larger population from which there is no substantive difference.

Pharmaceutical and biotechnology companies can accelerate successful development of orphan products by partnering with product development service providers with a culture of solving challenges and the scientific and regulatory expertise to navigate complex trials and approval processes.

The National Organization for Rare Disorders reports nearly 7,000 orphan diseases affecting nearly 30 million Americans. As more drug companies search for new approaches after mass-market drug revenues are lost to generic competition, orphan drug development is gaining momentum.

At Rho, we share a passion for discovering new treatments and have experience successfully helping companies navigate the FDA’s orphan product approval processes. But just like anything that sounds too good to be true, sound product development program decisions should stem from a keen understanding of the requirements and potential benefits of each approach. Selecting the right product development services partner can help deliver new treatments to improve and save lives as quickly as possible.

Click Here to View a Slideshow on Key Tips for Orphan Products