FSP model in clinical research industry: A natural progression and synergistic approach for FSO delivery gap mitigations for niche clinical studies and services

The dynamics of Clinical Research Organisation (CRO) outsourcing industry is rapidly changing. There has been inherent demand for experienced and well-trained resources in theindustry to overcome the challenges of resource attrition and high-cost involvement for maintaining the staff for short-duration projects. The issue is amplified by rapidly increasing Research & Development (R&D) costs and challenges of recruiting and retaining patients for clinical trials. Additionally, significant development in data aggregation; advanced mobile technology usage, advent of AI-enabled analysis tools as well as new risk management methodologies are rapidly changing the dynamics for collection of clinical trial data; source data verification; trial data monitoring, etc. This paves the path for an urgent re-look at the way in which core clinical research tasks are being outsourced by pharma companies.

In this ever-increasing complex environment, pharma companies are in desperate need for more flexible approaches and resourcing models, industry standardised systems and remote capabilities to deliver on their outsourcing requirements. The issue has been augmented by the ongoing COVID-19 pandemic, which has not only increased patient recruitment and retention challenges, but also hiring, training and retention of clinical staff. This problem statement is effectively addressed by complimenting the FSO outsourcing with Functional Service Provider (FSP) outsourcing model to provide cost-effective and agile clinical task delivery methodology for select study and task.

To substantiate this fact, is a recent research which shows that large biopharma companies’ use of FSP is growing at more than 13 per cent annually*. (*Applied Clinical Trials, Applied Clinical Trials-09-01-2020, Volume 29, Issue 9).

There are significant benefits for FSP model approach:

1. Cost effectiveness: For any specific service task, an individual hired is charging a fixed cost ( i.e. Cost To Company (CTC) — which is the fixed remuneration); however, there are many overhead costs like bonuses, gratuity, PF, seat cost, health insurance, taxes, electricity and other related overheads which considerably increases the resource cost significantly. FSP model is highly beneficial in these scenarios, as there is considerable cost saving as cost of resource identification; retention and maintenance is relatively quite reasonable and controlled in FSP model.

2. Risk reduction: For specific tasks or projects where resources are required for short time periods and in different country than sponsor HQ country, there is inherent risk of having various queries and scrutiny from government agencies, employment regulators, company law managing work councils, taxing authorities, etc. FSP proves its mettle here as it provides wider risk coverage by provisioning flexible full-time work force without binding payrolls and various direct and indirect costs.

3. Flexibility: Generally, all pharma companies have dependable and robust HR departments. However, sometimes, sudden and urgent staff augmentation requirement or specific task SME for time-bound tasks are difficult to hire. Here, the FSP model plays its role and provides the required flexibility in provisioning experienced staffing requirement and ensures flexibility to increase or decrease in the shortest possible timeframe- most importantly, it gives flex to downsize team and save CTC once the limited time task is completed.

4. Mutual governance ability: Many a times, oversight capabilities are limited in pharma companies, especially for the short duration/specific task projects. So, if required, FSP can be customised to include functional management services where a combined and structured mutual governance structure could be built in to serve the pharma company’s needs in more elaborate and mutually agreed fashion.

5. Expanding talent pool in targetted fashion: FSP enables pharma companies to expand in specific geographies or specific therapeutic areas in targetted manner. For example, if a sponsor company has a requirement for vaccine segment expertise in monitoring COVID-19 trial data in APAC countries, it would be inherent that the individuals working on this trial have relevant experience in this niche space. In such an instance, within a few months, the same can be achieved faster and efficiently by harnessing FSP model from specific CRO partners as compared to internal staffing.

Conclusion:
In conclusion, the FSP model is very apt and synergistic model and could strongly complement the existing “only FSO model” approach. This hybrid model could be implemented, if not for all, but in many CT studies, and, also as hybrid approach alongside with the FSO model for specific tasks such as monitoring, medical writing, data management; biostatistics, programming, etc. with comparatively low risk profile to pharma companies e.g. risk of fluctuating resource demand.

The traditional FSO model approach sometimes might encounter high turnover rates, inflexible approach due to unavoidable technical circumstances, and is usually costly for smaller sponsors and pharma companies. FSP provides a natural evolution and solution alongside FSO model by rendering services more affordable for mid-size and smaller regional pharma companies too. Thus, many pharma companies in the clinical development now are positively looking towards FSPs and forming synergistic partnerships alongside FSO model that better mitigate risks and provide positive outcomes.