In general, fasting condition is considered to be the most sensitive condition to detect a potential difference between two formulations (Test and reference or two test and one reference), however again this is not the thumb rule.

There are several factors which also needs to be considered before concluding if fasting or fed study condition is more appropriate or if both studies are recommended by agency. These factors include product solubility, physio-chemical characteristics, effect on food on solubility, site of absorption, type of formulation, product variability, metabolism and pharmacokinetic properties including gastric emptying, gastrointestinal pH, luminal metabolism etc. Detailed literature review and OGD recommendations required before jump in to the conclusion.

We had practically experienced that agency has accepted single study if strong supportive evidences based on pilot data or literature are provided. 

At C-trials such conditions come multiple time. We have advised many of the clients for making final decision based on the aforementioned factors which helps client to save economically a lot.

The two-stage design or add on design approach is accepted by regulatory agencies and should be predefined in the protocol with stoppage rule. Based on our knowledge, very few CROs have used this design approach and is not among their favourite approach since this consumes more time than conventional two-way crossover study. Two stages or add on also gives a second chance to modify sample size with some statistical penalty but it also helps when earlier pilot or pivotal data is not available or when intra subject variability is not known. Add-on designs, group sequential designs and adaptive two-stage sequential designs are currently accepted to demonstrate bioequivalence in various regulations. Designing such studies with different approaches are acceptable to regulatory agencies but needs good statistical understanding, confidence and knowledge on guidelines. Most important close relations with CRO is also required since study involves two stages with stop and start process which consumes time.

IVIVC tool is a surrogate for in-vivo bioavailability and with better understanding about the product characteristics and correct statistical method correlation, one can predict the in-vivo behaviour of the formulation. The main challenges that lie in establishing a correct IVIVC are inter subject variability related to pH, drug residence time in GI tract and viscosity effect of food which influences drug release and ultimately drug absorption

With due consideration of above factors using correct tool and having thorough understanding of formulation and bioequivalence, correct IVIVC prediction is possible. C-trials has performed multiple IVIVC and has in house formulation and bio experts. 

Yes, combining fasting study and steady state study are possible especially for EU submission for modified release formulations. Combining two studies together saves time and cost and also provides added advantage of using same population, which further lowers the intra subject variability which helps in passing BE study. However, it is important to note that this approach should be carefully defined in the protocol with due consideration of sampling time point, blood loss, ethical and safety consideration.

Calculating sample size is a vital step during the planning of a biostudy in order to ensure the desired power for detecting clinically meaningful differences. As a practise most of the CROs reply on SAS calculation which is based on intra subject CV and T/R Ratio obtained from literature or from pilot/pivotal study they have conducted for another sponsor. Using this data is not correct since each formulation is different and hence sample size will also be different for each product. SAS sample size calculation gives idea of probable sample size.

e.g. In case where study which has passed with 24 subjects, SAS output has suggested sample size of 56. This is because sample size was calculated based on only ISCV and T/R Ratio without considering pilot or pivotal study output results.

It is very important to analyse the pilot study data or licensed data and then decide what should be the sample size for the study. Only relying upon statistical output may have a smaller number of subjects leading to study being under power and may expose the study to potential risks. Similarly, if the number of subjects is unnecessarily large may lead to higher expenses and extended timeline.

Though calculating sample size looks to be simple process but several factors should be considered to arrive to an appropriate sample size like – study objective, study design, end point, power, test-to-reference ratio, population, potential dropouts, washout period, pilot study data, location where earliest study was done, adverse reaction reported in pilot study, change of Test or Reference Batch etc.

C-trials team supports sponsor by reviewing the available study data such as pilot bioequivalence data, relevant pharmacokinetic data on reference product, in vitro dissolution data, and define possible strategy for pivotal study keeping in mind if the product is In licensed dossier, or pilot or pivotal study in house develop formulations.