Harnessing Asia’’s clinical trial potential

2013 was a challenging year for the clinical research sector in India, and the situation seems even tougher moving into 2014. Media reports of a Government ruling in December 2013 that all ethics committees that approve clinical trials need to be accredited as well as registered, is definitely moving clinical research in India in the right direction. However, in the short term, this will further shrink the currently available site pool and increase start-up timelines in India. Data from the Clinical Trial Registry — India (CTRI) shows that only 114 of the 228 phase II and III clinical trials that were registered in 2013 are currently open to recruitment.1 The slowdown in approvals and the newer regulations being imposed are making it next-to-impossible for pharmaceutical firms to complete their clinical development programmes on schedule and is driving them to look at the rest of the Asia Pacific region and even to the West to meet their clinical trial needs.2

The rest of the Asia Pacific region, with its sizeable population,3 represents a significant potential patient pool for these clinical trials to tap into.4 The changing burden of disease trends in east Asia and the Pacific region, which are moving away from communicable diseases and more to non-communicable and chronic diseases, mirroring global trend5, represent opportunities for investigational products aimed at both Asian and global markets and for clinical trial participants, offering them more treatment options.

In the early stages of the clinical trial process, getting off to the right start can translate into dollars on the corporate bottom line. For each day a timeline slips, the estimated loss in operational costs alone is estimated to be around $35,0006. Also any delay will impact on when the new medicine may be available to patients.

Ensuring the best study strategy in a region with diverse healthcare environments from the established clinical trial systems in Japan, South Korea and Taiwan at one end to the relatively new systems and sites in Vietnam, Indonesia and Cambodia on the other, presents some challenges, but can also bring big opportunities when the potential is effectively harnessed. Three key resources that can be leveraged to achieve this are: current and comprehensive local intelligence that supports innovative site identification methodologies; qualitative and quantitative data allowing data-driven feasibility assessment at country, site and investigator level; and strategic site relationships promoting operational efficiency and effective site management to ensure data integrity and patient safety. These resources can support data-driven decision making to arrive at the best country mix and the right sites and investigators for clinical trials.

Innovative site identification methodology

The traditional site identification process involves pinpointing sites once a study protocol is in hand. In a rapidly growing clinical trial environment like Asia, this process can often lead to settling an appropriate combination of ‘currently known and available’ countries and sites for studies, rather than best possible ones. There is tremendous diversity in experience levels of the countries in the region, with Korea and Taiwan highly sought after for their quality and delivery, while Thailand, Vietnam and Indonesia, are largely untapped for their clinical trial potential. Knowledge of the available site universe in each country early on in the game can be critical in helping ensure that the most appropriate sites are included in the study, those with promise are considered, and inappropriate ones are excluded. The process involves taking a ‘ground-up’ approach to site identification. An upfront investment in time and local resources is necessary to map all possible clinical trial sites in a country’s healthcare system and prioritise these sites based on their capabilities and potential to conduct high quality work across the various stages of clinical trials across the therapeutic spectrum7.

The local intelligence generated then helps determine the type of studies the country can do, based on factors such as the type and number of patients accessible, interest levels and infrastructure available at the sites, ethics committee approval processes and their influence on start-up timelines, and other site-specific nuances. This also identifies the maximum number of sites potentially available, and provides a heads-up on any site development activity needed to ensure operational efficiency and patient safeguarding. This is especially important when in bringing down start-up costs and initiating trials in the minimum number of countries necessary.

Using Thailand as an example, the country site mapping methodology was presented at the Drug Information Association (DIA) Annual Conference in Boston in 2013. The poster showcased Thailand’s 1,200 possible clinical trial sites, including the major medical school hospitals in highly populated cities with the capabilities to take on phase II-IV clinical trials across therapeutic areas. Not surprisingly, 60 per cent of the country’s sites reside in a primary healthcare setting, demonstrating the potential of the country for studies involving chronic illnesses such as diabetes and hypertension, and also vaccine trials6.

In South Korea, on the other hand, the Ministry of Food and Drug Safety (MFDS) approves sites for conducting clinical trials in the country. There are currently 164 sites approved for conducting clinical trials, representing the maximum available number of sites in the country8.

In order to understand the potential at the therapeutic area and indication level, the sites mapped can be further interrogated. If we look deeper at the 164 Korean sites, 74 have conducted an oncology study (phase I-IV) at some time based on data from the Korean Food and Drug Administration (KFDA) Clinical Trial Registry, including 36 in non-small cell lung carcinoma (NSCLC)9. This therapeutic area and indication level mapping provide a clear picture of the available site pool that can then be evaluated by clinical operations teams for their suitability for studies. This also helps the site strategy development during the very early planning and budgeting stages as well as when the sites are actually being assessed at the time of site selection.

Data-driven feasibility assessments (countries, sites and investigators)

Data-driven feasibility analysis is an essential step when the study protocol is being drafted and the study site strategy is being developed. This step involves an initial assessment to determine whether a clinical trial can be executed effectively10. In Asia Pacific, as in other regions, this could consist of assessing a company’s internal database, which includes information from previous clinical trials, investigator outreach and data collected from other public and proprietary sources. Key considerations for a robust feasibility in a diverse healthcare environment include the protocol’s inclusion and exclusion criteria, regulatory considerations and local nuances, competition from other trials in the same indication, the marketing strategy of the company, and the clinical site’s access to the target patient population11,12. As an example, consider an NSCLC study looking for countries within the region.

According to Globocan 2012 data, China ranks first in the world for the incidence of lung cancer13, making it a potentially high priority country for a NSCLC study. However, when other factors are taken into account, such as the high number (127) of currently on-going studies14, which often results in lower recruitment rates, and the relatively long start-up time of 12 months that China currently needs to start recruiting4 – then China moves many spaces down the priority list, giving way to countries such as Thailand and South Korea. Given the limited experience of some countries in the region and the absence of quantitative data, qualitative data such as feedback from potential investigators can be used.

To further aid data-driven decision-making, and to support the experts who provide a critical review of the data and recommendation for actions, quantitative data can be run through customised algorithms and the results suitably visualised, allowing a comparative analysis. Quantitative data could include data from previous clinical trials, prevalence and incidence data, site and country start up timelines, and drug reimbursement regulations. An example of such visualisation is depicted in Figure 5. This process provides the ability to objectively ascertain the best countries, sites and investigators to place a trial in a very dynamic region like Asia.

Performance Index Score (PIS) = Score for each site based on the customised algorithm. In the example above, the site with the highest PSI would be the best site. The three different shades of blue indicate the three levels of sites, the darkest blue (far right) being the priority sites with the highest PSI.

Integrating data and technology to provide better insights is the way forward in a ‘Big Data’ world. The Quintiles Infosario system and Pfizer’s TIBCO Spotfire data visualisations are all examples of visualisation tools1.

Strategic site relationships

Knowing which are the best sites and having a well-written protocol does not necessarily amount to a good site strategy if the best sites are busy with other competing trials and cannot take on the study. Strategic alliances with high-performing sites provide the opportunity to plan ahead, offering a better chance at securing the studies at these key sites in a highly competitive environment. Seoul National University Hospital (SNUH), one of the premium hospitals and research institutes in South Korea, currently has 380 ongoing clinical trials2. High-performing sites also need constant coaching and guidance to stay at the top of their game. Active site management, focused on engaging with the site’s higher management to drive better productivity, delivery and quality further ensures that these remain the best sites to have in a study. It has been demonstrated that with active management, such sites can recruit 50 per cent more than normal sites3. The biopharmaceutical and CRO industries are both moving in the direction of strategic alliances with key sites in the region4,5, providing opportunities for sites to select the best studies to offer their patients and for sponsors of clinical trials to improve study start-up and recruitment timelines.

As more clinical trials move into the Asia Pacific region over the next few years, it is becoming increasingly imperative to plan ahead and ensure that countries are ready to take on the studies and that studies are designed to fit the region. The importance of the right operational strategy being implemented at the very beginning highlights the importance of a consolidated Asia site strategy. The three key resources of qualitative and quantitative data, up-to-date local intelligence, and strategic site relationships all help set a solid foundation for the study site strategy. Close collaboration with other operational groups, such as site start up, clinical monitoring resources, project management and central lab services, can ensure the delivery of a successful clinical trial in this region.

References:
1. Clinical Trials Registry – India (CTRI), Accessed on 3Jan2014 http://ctri.nic.in/Clinicaltrials/advancesearchmain.php
2. The Financial Times, Pharmaceuticals,’India ruling on drug trials injects fears for industry’s health’, 18Nov2013, Accessed 3Jan2013, http://www.ft.com/intl/cms/s/0/76335e22-4d03-11e3-9f40-00144feabdc0.html#axzz2pIM7toOm
3. Asia Population 2013, World Population Statistics, 20May2013, http://www.worldpopulationstatistics.com/asia-population-2013/
4. PricewaterhouseCooper, ‘The changing dynamics of pharma outsourcing in Asia – Are you adjusting your sights,’ 2008. Accessed 6Jan2014 http://www.pwc.com/en_GX/gx/pharma-life-sciences/pdf/change_asia_10_08_08.pdf
5. Institute for Health Metrics and Evaluation, The Global Burden of Disease: Generating Evidence, Guiding Policy, East Asia and Pacific Region Edition, 2013. http://issuu.com/ihme/docs/wb_gbd_report__east_asia___pacific?e=2626063/4701958#search
6. Digitome 2011, Digital Health: Clinical Trials, Accessed 6Jan2014 http://digito.me/resources/clinical-trials-are-going-digital/
7. Saldanha LM, Current Scenario of Clinical Research Sites in Thailand: A Ground Up Approach to Clinical Site Selection in Emerging Countries, Poster Presentation Drug Information Association Annual Conference, Boston, 2013. http://www.diahome.org/~/link.aspx?_id=7FA8279B1DC940CA8109CDF6F0E19B11&_z=z
8. http://www.mfds.go.kr/index.do?seq=7221&mid=1043 accessed 6Jan2013
9. http:// drug.mfds.go.kr /html/menuLinkBody.jsp?p_menuId=0202#1 accessed 6Jan2014
10. Turner JR. New Drug Development: An Introduction to Clinical Trials, 2nd ed. New York, NY: Springer; 2010
11. Wai K, Saldanha LM, Lansang EZ et al Case series of feasibility considerations that impact operational delivery strategy in the highly competitive rheumatoid arthritis space in Asia, Open Access Journal of Clinical Trials 2013:5 33–38
12. Lansang EZ, Tan K, Nayak S et al Key feasibility considerations when conducting vaccine clinical trials in Asia–Pacific countries Vaccine: Development and Therapy 2013:3 1–9
13. Globoban 2012, ‘Estimated Incidence, Mortality & Prevalence Worldwide 2012’, Accesses 6Jan2014. http://globocan.iarc.fr/Pages/summary_table_site_prev_sel.aspx
14. http://www.infinata.com/biopharma-solution/by-product/biopharm-clinical.html Accessed 5Jan2014
15. http:// www.intel.sg/ content/dam/www/public/us/en/documents/white-papers/big-data-visualization-turning-big-data-into-big-insights.pdf Accessed 7Jan2014
16. http://www.quintiles.com/ data-driven-difference/ Accessed 7Jan2014
17. http:// www.snuh.org/english/ snuh/snuh03/sub02/index2.jsp, Accessed 6Jan2014
18. http://www.quintiles.com/ services/capabilities/clinical/ patient-investigator-recruitment/ accessed 03 Jan2014
19. http://www.quintiles.com/library/press-releases/quintiles-partners-with-the-seoul-national-university-hospital/Accessed 6Jan2014
20. http:// www.ntu.edu.tw/ engv4/ highlights /2012/he121201_2.html accessed 6Jan2014