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Pilot studies and their role in research design

In order to obtain higher quality outcomes, good research requires relevant experimental designs and accurate performances. Pilot studies, commonly known as feasibility studies encompass mini versions of a full-scale study or are known to accomplish pre-testing of concerned research instruments or schedules (Malmqvist et al. 2019). It assists in planning and relative modification of the main study. It is an integral element of a good study design. A major advantage of conducting a pilot study can be around how it provides warnings in advance, regarding the drawbacks of the research or ways in which projects could fail. It helps in noting places where protocols of research are not followed, or proposed instruments and methods are complicated or inappropriate. Out of several reasons highlighting the significant importance of Pilot studies, convincing funding bodies are also necessitated regarding the avenues of the research proposition. They play a key role in developing refined interventions, procedures and assessments. Grant reviewers, investigators, and other stakeholders should be aware of the appropriate role, and essential elements and interpret pilot studies correctly. Process validation is essentially the collection and efficient evaluation of data, from the stage of process design throughout production. It establishes scientific evidence on how a certain process can be capable of delivering quality enriched products consistently. In 2011, FDA has introduced General practices and principles for process validation, promoting modern manufacturing principles, process improvement, sound science and innovation and risk mitigation strategies (Kaza et al. 2019). Pilot programs are designed as scale up operations that are conducted on products or associated processes before it leaves the laboratory to be accepted by full-scale manufacturing units. The number and size of laboratory pilot batches can be different in response to equipment, raw material or pharmaceutical ingredient availability. Pilot production batches scale products and processes to a higher magnitude.

Pilot studies also validate the process of assessing the exclusion and inclusion criteria of participants in the main study, involve the preparation of interventions and drugs, and stores and tests instruments aiding measurements. Pilot studies assess the blinding and randomization to be properly executed, with detailed procedures for storage, preparation and delivery. The uniformity in appropriate blinding and demographic traits based on the plans of the researcher and the participant's understanding of randomization is also assessed. Pilot studies test the adequacy of the research instruments and assess the success of proposed approaches to recruitment Identification of logistical problems and estimation of outcome variability, determining sample size, amalgamating preliminary data is brought about (Lowes and Brown 2019). Researchers can recruit subjects and can obtain their consent for participation. Consequently, the appropriateness of the consent, time for receiving written consent, recruitment rates, and the number of researchers or assistants can be determined.

Pilot studies can contain certain limitations as well. These involve the chances of formulating inaccurate assumptions or predictions based on pilot data, issues arising due to contamination and funding problems (Avery et al. 2017). Completion of a pilot study would not necessarily guarantee the success of full-scale surveys as they do not have a statistical foundation while being based on small digits. Contamination can arise where data from pilot studies are incorporated into the main results. Scientists predominantly argue over how data are not utilized for testing hypotheses or included in data from actual studies in the result reports. Attained data can be flawed when problems with research tools arise to modify contents and findings in pilot studies. Pilot studies are often not reported as publication bias can emerge out of the tendency of journals to accept statistically significant results stringently.

The benefits and limitations of pilot studies

 Study Size-Influencing conclusions; CI- Confidence Interval

Fig 1: Study Size-Influencing conclusions; CI- Confidence Interval

Source: (In 2017)

“Continuous process verification” (CPV) is the 3rd stage as per the guidelines of FDA process validation and represents a significant sector in bioprocessing. It validates the bioprocess and is inevitably subjected to alterations in parameters like supplies, equipment and raw materials (Das et al. 2018). It is essentially a study format with various attributes that should be controlled regularly and monitored during the GMP bioprocess lifecycle. Reviews at regular intervals would critically ensure changes to not influence current results. The creation of a continued verification plan would not only gain compliance with regulatory bodies but minimalize batch discards, mitigate vulnerabilities in the process and find possibilities for improvement. Various considerations concerning the inclusion of specific data in the plan, frequency of attributes to be monitored, and the standard of statistical sophistication are also discussed. Importance is levied on the significance of data integrity where transfer of various data sources can be to a centralized source is critically ensured. The data analysis should be robust and reveal the right signals for investigation. As the 3rd stage in the lifecycle processes maximum data, the importance of enhancement of control strategies on an ongoing basis is observed. The protocol-based first section of the stage assessment lays the foundation for moving into standard operating procedures (Kim et al. 2021). A preliminary assessment with substantial data is recommended before monitoring routines. The CQA (critical quality attribute) variability sources can be environmental status, machine, man and measurement (Gray 2018). Control strategies essentially encompass a planned set of regulations derived from the present process and product understanding and assuring product quality and performance. It ensures that commercial processes can consistently continue to produce acceptable products. Biopharmaceutical developments also culminate through the control strategy or comprehensive package involving process controls, and analytical procedures. The establishment of scientific evidence in the next stage of PPQ or “Process performance qualification” needs the process to be reproducible and consistently deliver efficient products. In the last stage as well, CPV or validation by process verification gives an opportunity for improving process control through the product lifecycle. Manufacturers are expected to understand, detect and effectively control variation before development throughout commercial manufacturing. The “CMC strategy forum” provides an avenue for biotechnological product discussion where meetings focus on control, manufacturing and chemistry issues throughout product lifecycles and foster collaborative regulatory and technical interactions (Algorri et al. 2021). Control strategies are meant to reflect the totality of elements, including combinations of process design, development and specifications, facility controls, raw material controls, in-process controls and proper monitoring of relevant attributes and parameters.

 Evolution of Control strategy through CPV

Fig 2: Evolution of Control strategy through CPV

Source: (Suzuki et al. 2021)

A consortium of biotechnological companies promotes industry-wide studies for gaining insights on common viral contaminants, and for reducing calamities with batch cultures in manufacturing units. Recombinant protein therapy, plasma products and vaccines need to implement long records of safety as the utilization of cell culture remain susceptible to viral contamination (Mao and Chao 2019). It can be concerning as in the case of mammalian cell cultures, could be potentially replicating human pathogens. Cleaning validation studies emerge out of key contamination sources like manufacturing multiple biological products when “change-over” is necessary when animal origin free and animal-derived supplies are used in the facility. Using plant-derived materials act as a source of adventitious agents and mycoplasmas. Operations inside viral manufacturing constructs require global regulatory bodies to integrate cleaning validation. Other typical contaminants for validation studies include host cell proteins, lipids, DNA nuclei, endotoxins, carbohydrates, detergents, viruses, TSEs, and mycoplasmas, to name a few.

Process validation and its significance

Selecting model microorganisms is a critical portion of developing inactivation or removal protocols. The selection considers the origin and nature of the raw materials and equipment used in the process of production, for the species to represent environmental, material, and human-derived microbial flora while offering antimicrobial resistance. The model viruses should be known and research-based evidence should be promoted. Products also encompass viruses with DNA or RNA genomes, without or with lipid membranes, and range in varying sizes. Processes enable should be able to remove or inactivate a wide range of viruses. Viruses of critical concern like HBV, HIV or HCV are transmitted through plasma products and are vitally fatal. Another selection criterion is the ability for it to grow in high titre stocks in both standard cell culture and microbiological media. All viruses should yield low titres than assumed in HI tests with WHO reference kits or ferret antiserum. There is overall ease of detection in reliable and sensitive assays. The notable properties recorded are the concentration of precipitation agents, temperature, protein elution profiles, flow rates and buffer volumes for convenience in production cells. Depending on the quantity of positive specimens, epidemiological and available clinical information should be primarily considered for relevant biosafety requirements (Lissabet et al. 2019). Viruses that are sub-typable, for instance, influenza A positive which cannot be identified and found to be circulating should be sent for WHO CC (Collaborating Centre) checks quickly (Hampson et al. 2017). During periods of surveillance like that of the pandemic, samples sent should be based on WHO recommendations. Utilization of efficient cryovials for storage of specimens and dry ice transport is mandatory.

 ommon Viruses utilized in Cleaning Validation studies

Figure: Common Viruses utilized in Cleaning Validation studies

Source: (Jornitz 2019)

References

Algorri, M., Abernathy, M.J., Cauchon, N.S., Christian, T.R., Lamm, C.F. and Moore, C.M., 2021. Re-Envisioning Pharmaceutical Manufacturing: Increasing Agility for Global Patient Access. Journal of Pharmaceutical Sciences.

Avery, K.N., Williamson, P.R., Gamble, C., Francischetto, E.O.C., Metcalfe, C., Davidson, P., Williams, H. and Blazeby, J.M., 2017. Informing efficient randomised controlled trials: exploration of challenges in developing progression criteria for internal pilot studies. BMJ open, 7(2), p.e013537.

Das, P., Kumar, S.R. and Maity, A., 2018. The New Paradigm of Pharmaceutical Process Validation-Continuous Process Verification.

Gray, V.A., 2018. Power of the dissolution test in distinguishing a change in dosage form critical quality attributes. AAPS PharmSciTech, 19(8), pp.3328-3332.

Hampson, A., Barr, I., Cox, N., Donis, R.O., Siddhivinayak, H., Jernigan, D., Katz, J., McCauley, J., Motta, F., Odagiri, T. and Tam, J.S., 2017. Improving the selection and development of influenza vaccine viruses–Report of a WHO informal consultation on improving influenza vaccine virus selection, Hong Kong SAR, China, 18–20 November 2015. Vaccine, 35(8), pp.1104-1109.

In, J., 2017. Introduction of a pilot study. Korean journal of anesthesiology, 70(6), p.601.

Jornitz, M.W. ed., 2019. Filtration and purification in the biopharmaceutical industry. CRC Press.

Kaza, M., Kara?niewicz-?ada, M., Kosicka, K., Siemi?tkowska, A. and Rudzki, P.J., 2019. Bioanalytical method validation: new FDA guidance vs. EMA guideline. Better or worse?. Journal of pharmaceutical and biomedical analysis, 165, pp.381-385.

Kim, E.J., Kim, J.H., Kim, M.S., Jeong, S.H. and Choi, D.H., 2021. Process analytical technology tools for monitoring pharmaceutical unit operations: a control strategy for continuous process verification. Pharmaceutics, 13(6), p.919.

Lissabet, J.F.B., Belén, L.H. and Farias, J.G., 2019. AntiVPP 1.0: A portable tool for prediction of antiviral peptides. Computers in biology and medicine, 107, pp.127-130.

Lowes, S. and Brown, M., 2019. Bioanalytical method validation guidance language and a decade of progress. Bioanalysis, 11(07), pp.587-593.

Malmqvist, J., Hellberg, K., Möllås, G., Rose, R. and Shevlin, M., 2019. Conducting the pilot study: A neglected part of the research process? Methodological findings supporting the importance of piloting in qualitative research studies. International Journal of Qualitative Methods, 18, p.1609406919878341.

Mao, H.H. and Chao, S., 2019. Advances in vaccines. Current Applications of Pharmaceutical Biotechnology, pp.155-188.

Witcher, M.F., 2018. Integrating Development Tools into the Process Validation Lifecycle to Achieve Six Sigma Pharmaceutical Quality. BioProcessing Journal, 17.

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