Assistant Manager - R&D

Assistant Manager - R&D Interview Questions and Answers

Updated 13 Jul 2025

Asked in Zentiva

6d ago

Q. How do you start method development of an unknown compound by HPLC for Related Substances (RS) analysis?

Ans.

To start method development of unknown compound by HPLC for RS, one should consider various factors.

  • Identify the properties of the compound such as polarity, solubility, and stability

  • Choose the appropriate column and mobile phase based on the properties of the compound

  • Optimize the chromatographic conditions by adjusting the flow rate, gradient, and temperature

  • Validate the method by checking the specificity, linearity, accuracy, and precision

  • Compare the retention time and peak...read more

Asked in Zentiva

4d ago

Q. In force degradation studies, what steps do you take if mass balance is not achieved?

Ans.

If mass balance is not achieved in force degradation, investigate the cause and repeat the experiment.

  • Check for any errors in the calculations or measurements.

  • Verify the accuracy of the instruments used.

  • Repeat the experiment to ensure the results are consistent.

  • Investigate the possibility of degradation pathways that were not accounted for.

  • Consult with colleagues or experts in the field for guidance.

  • Document all steps taken to address the issue for future reference.

Asked in Zentiva

6d ago

Q. How can peak tailing be reduced and resolution improved?

Ans.

To reduce peak tailings and improve resolution, one can optimize the chromatographic conditions.

  • Adjust the mobile phase composition and pH

  • Optimize the column temperature and flow rate

  • Use appropriate sample preparation techniques

  • Consider using a different column or stationary phase

  • Ensure proper calibration of the instrument

  • Perform regular maintenance and cleaning of the equipment

Asked in Zentiva

5d ago

Q. How does QDA work, and what are its working principles?

Ans.

QDA is a statistical method used for classification and prediction of data based on its attributes.

  • QDA stands for Quadratic Discriminant Analysis.

  • It is a supervised learning algorithm used in machine learning.

  • It is based on Bayes' theorem and assumes that the data follows a Gaussian distribution.

  • QDA calculates the probability of a data point belonging to a particular class based on its attributes.

  • It then assigns the data point to the class with the highest probability.

  • QDA is ...read more

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