Each of us has, or will be, touched by cancer over the course of our lives.
Cancer is the leading cause of death worldwide with an increase in cancer-related deaths to climb from 8.2 million in 2012 to 22 million over the next two decades1.
In the United States alone in 2016, an estimated 1,685,210 new cases of cancer will be diagnosed and 595,690 will die from the disease2. More than a third of us will be diagnosed with cancer at some point3. Each new diagnosis of cancer underscores the critical importance of finding more effective, less toxic, and curative treatments for cancer.
The bio/pharmaceutical industry is making significant investments in developing efficacious treatments. And this investment can be optimized with intermediate steps to shorten the drug development process.
Cancer Treatment Development
There are more drugs in development for cancer than any other disease area. In the first half of 2016,718 (28%) of new clinical trials targeted cancer (Figure 2); a 14% increase compared to the first half of 20154 . The second leading area of study in the first half of 2016, the central nervous system, accounted for 321 clinical trials, less than half of those focused on cancer.
Unfortunately, compounds for oncology indications cost more to develop than drugs for other indications. Further, oncology compounds are more likely to fail to reach the market, with a likelihood of approval of only 5.9% (see Figure 4). However, if they do reach the stage of submission for licensure, “oncology drugs are approved faster than any other therapeutic area”5.
It is expensive to bring a new drug to market. Across therapeutic areas, “the cost of bringing a single product to market is estimated to be between $1.2 and 1.8 billion” and increases in costs have not corresponded with increases in product approvals. In fact the opposite is true – new data indicate that the number of drugs invented per billion dollars invested in R&D has been nearly cut in half every nine years for the last fifty6.
In order to optimize development of new treatments for cancer, we must shorten the time of development, while reducing the overall costs and the number of failed attempts. We need to be smarter and more innovative about how we design and execute oncology studies. Obtaining data in Phases 1 and 2 that allow for more robust, data-driven go/no-go decisions with a higher degree of confidence is paramount.
Standard Oncology Clinical Trial Scenario
In traditional oncology clinical trials, the Phase 1 study(ies) is focused on patient safety. The study(ies) enrolls “all comers” that meet the inclusion criteria.
At most, the clinical trial work is in addition to the primary focus of treating patients in the clinical oncologist’s office setting. The investigator and site staff are required to juggle their primary responsibilities of clinical and office work with those required by the trial7,8.
From one office to the next, variability in execution exists, with potential implications for the quality of data collected. In addition, when patients enrolled into the trial are seen or admitted into the hospital, the investigative site clinical staff have the added responsibility of trying to track down and obtain the additional source (admitting diagnosis, adverse events, concomitant medications, radiology reports, lab results, normal ranges, etc.) which can be cumbersome and problematic.
A Revised Scenario That’s Win - Win
- More targeted enrolment in early phases (rather than all comers) with biomarkers whenever possible
- Adaptive designs so that what is not working can be minimized and what is working can be optimized
- Collect as much data as possible on the mechanism of action (PK, PD, tissue, etc.) or do hybrid designs to get Phase I and II data in one trial.
While the “all comers” approach is an excellent way to collect safety and dose escalation data relatively easily, it removes the ability to get any early indication (albeit not powered to reach significance) of efficacy. When possible (as this is not always an option), biomarkers will ideally be available for inclusion and exclusion criteria to further identify patients who are most likely to benefit from the study treatment. As seen in the Figure 4, this addition has a significant impact on the success rate of a study, with a “three-fold increase in the likelihood of approval from Phase I”. By focusing the early design on a specific tumor type (driven from preclinical outcomes), biomarkers for inclusion (when available) AND implementing an adaptive design, trials become potentially much more informative, and trends are noticed more rapidly, all with fewer patients.
Sponsors and CRO partners will ideally collaborate early on during the study design phase to discuss options and the best approach for any given trial.
SGS has proven success in assisting sponsors with trial optimization to reduce cost, increase speed, and ultimately, have the best data possible. This starts with a quality, streamlined and focused development plan involving all of the critical stakeholders so that a full and robust picture is known up-front. This includes modelling and simulation intelligence, pharmacokinetics, feasibility, regulatory, program management, medical monitoring among other factors, from the first study through to post marketing. SGS ensures that each area is covered so that there are not only no surprises, but to ensure that the most innovative solution has been developed, tailored to the desired outcome with a quality design approach. As a mid-sized CRO, SGS has the agility and expertise to do what is needed – inform early and confident go/no-go decisions. SGS treats every project as if it were its own agent in development. While it’s a huge help, design will not answer all of the challenges. As everyone in clinical research is well aware, execution is key to success.
4. Control for and limited data variability
Unlike the traditional setting of conducting trials at oncologists' offices, SGS takes a win-win approach.
The SGS approach is unmatched by it's peers and provides for more control of execution, reducing variability in data, and most critically, the best possible care for the patients who enroll into the studies at a critical time in their care and life.
SGS has several hospital-embedded research units focused on the conduct of early phase work, and specifically that of oncology.
These research units aren't just another doctor's office trying to manage both responsibilities; rather the clinical trial is the sole job of the SGS team. The one and only focus is to ensure trials are run at the highest possible standard and that patients receive care that is second to none.
SGS’s units use the same procedures, leverage and collaborate together to utilize the same source worksheets, workflows, and are continually in communication with each other to capitalize on each other’s efficiencies. This leads to more consistent assessments, collection and processing of samples, treatments all ultimately translating to higher quality and reduced variability in the data collected for analysis.
In addition, because these research units are hospital-based, in the event of a patient requiring special supportive care, or being admitted, they are still being seen by their study doctor. This eliminates the need to chase after source from other locations or from other treating teams that may not have even been aware that the patient is on a clinical study. In addition, the labs, pathology, any imaging modality etc. required for inpatient care is that which is already utilized for the research unit. There is no variability among labs or equipment to worry about as it is already part of their source file.
The end benefits sponsors and most critically – the patients.
The sponsor gains better, faster implementation, collecting and delivering higher quality data with less variability; reducing the failure rate and overall program spend, informing more confident early go/no-go decisions.
For the patients all over the world who need a better option – each individual patient gets unparalleled care, and contributes more to the overall end goal of everyone finding a cure that much sooner.
Janelle Johnson, MBA, PMP
Head Project Management - North America, Oncology Project Director
SGS, Life Sciences - Clinical Research
1 Cancer Statistics
2 cancer.gov and the Surveillance, Epidemiology, and End Results Program (SEER),
3 SEER Stat Fact Sheets: Cancer of Any Site
4 Biopharm Insight CRO Report 2Q 2016
5 Clinical Development Success Rates 2006-2015
6 Right Drug, Right Patient: Streamlining Clinical Trials to Speed Drug Development
7 Keys to Success with Clinical Trials
8 Education and Training for Health Professionals
Fig 1: SEER Stat Fact Sheets: Cancer of Any Site
Fig 2: Biopharm Insight CRO Report 2Q 2016
Fig 3: Key Facts - Dying for a cure
Fig 4: Trial Watch: Phase II and Phase III attrition rates 2011–2012
Fig 5: Clinical Development Success Rates 2006-2015