Interview questions

What are the therapeutic areas you worked earlier?        

There are so many diff. therapeutic areas a pharmaceutical company can work on and few of them include, anti-viral (HIV), Alzheimer’s, Respiratory, Oncology, Metabolic Disorders (Anti-Diabetic), Neurological, Cardiovascular. Few more of them, include….  central nervous system,Neurology,Gastroenterology,Ophthalmology, Orthopedics and pain control,Pulmonary,Vaccines,Dermatology,Gene therapy,Immunology etc…

Q-2? Can you tell me something about your last project study design?                If the interviewer asked you this question, then you need to tell that your current project is on a phase-1 study (or phase-2/Phase-3). You also need to tell about the name of the drug and the therapeutic area of it. Here are some more details you need to lay down in front of him…

a) Is it a single blinded or double-blinded study?
b) Is it a randomized or non-randomized study?
c) How many patients are enrolled.
d) Safety parameters only (if it is a phase-1)
e) Safety and efficacy parameters if the study is either Phase-2,3or 4.

Q-3 What are your responsibilities?

some of them include,not necessarily all of them…

· Extracting the data from various internal and external database (Oracle, DB2, Excel
spreadsheets) using SAS/ACCESS, SAS/INPUT.
· Developing programs in SAS Base for converting the Oracle Data for a phase II study into SAS datasets using SQL Pass through facility and Libname facility.
· Creating and deriving the datasets, listings and summary tables for Phase-I and Phase-II of clinical trials.
· Developing the SAS programs for listings & tables for data review & presentation including adhoc reports, CRTs as per CDISC, patients listing mapping of safety database and safety tables.
· Involved in mapping, pooling and analysis of clinical study data for safety.
· Using the Base SAS (MEANS, FREQ, SUMMARY, TABULATE, REPORT etc) and SAS/STAT procedures (REG, GLM, ANOVA, and UNIVARIATE etc.) for summarization, Cross-Tabulations and statistical analysis purposes.
· Developing the Macros at various instances for automating listings and graphing of clinical
data for analysis.
· Validating and QC of the efficacy and safety tables.
· Creating the Ad hoc reports using the SAS procedures and used ODS statements and PROC TEMPLATE to generate different output formats like HTML, PDF and excel to view them in the web browser.
· Performing data extraction from various repositories and pre-process data when applicable.
· Creating the Statistical reports using Proc Report, Data _null_ and SAS Macro.
· Analyzing the data according to the Statistical Analysis Plan (SAP). · Generating the demographic tables, adverse events and serious adverse events reports.

Q-4 How many subjects were there?
Subjects are nothing but the patients involved in the clinical study.
Answer to this question depends on the type of the study you have involved in.
If the study is phase1 answer should be approx. between 30-100.
If the study is phase2 answer should be approx. between 100-1000.
If the study is phase3 answer should be approx. between 1000-5000.

Q-5 How many tables, listings and graphs?
Can be in between 30-100 (including TLG’s).

Q-6 Can you explain something about the datasets?
DEMOGRAPHIC analysis dataset contains all subjects’ demographic data (i.e., Age, Race, and Gender), disposition data (i.e., Date patient withdrew from the study), treatment groups and key dates such as date of first dose, date of last collected Case Report Form (CRF) and duration on treatment. The dataset has the format of one observation per subject.
LABORATORY analysis dataset contains all subjects’ laboratory data, in the format of one observation per subject per test code per visit per accession number. Here, we derive the study visits according to the study window defined in the SAP, as well as re-grade the laboratory toxicity per protocol. For a crossover study, both the visit related to the initial period and as it is related to the beginning of the new study period will be derived. If the laboratory data are collected from multiple local lab centers, this analysis dataset will also centralize the laboratory data and standardize measurement units by using conversion factors.
EFFICACY analysis dataset contains derived primary and secondary endpoint variables as defined in the SAP. In addition, this dataset can contain other efficacy parameters of interest, such as censor variables pertaining to the time to an efficacy event. This dataset has the format of one record per subject per analysis period.
SAFETY can be categorized into four analysis datasets:
VITAL SIGN analysis dataset captures all subjects’ vital signs collected during the trial. This dataset has the format of one observation per subject per vital sign per visit, similar to the structure for the laboratory analysis dataset.
ADVERSE EVENT analysis dataset contains all adverse events (AEs) reported including serious adverse events (SAEs) for all subjects. A treatment emergent flag, as well as a flag to indicate if an event is reported within 30 days after the subject permanently discontinued from the study, will be calculated. This dataset has a format of one record per subject per adverse event per start date. Partial dates and missing AEs start and/or stop dates will be imputed using logic defined in the SAP.
MEDICATION analysis dataset contains the subjects’ medication records including concomitant medications and other medications taken either prior to the beginning of study or during the study. This dataset has a format of one record per subject per medication taken per start date. Incomplete and missing medication start or stop dates will be imputed using instructions defined in the SAP.
SAFETY analysis dataset contains other safety variables, whether they are defined in the SAP or not. The Safety analysis dataset, similar to Efficacy analysis dataset in structure, consists of data with one record per subject per analysis period to capture safety parameters for all subjects. It is crucial to generate analysis datasets in a specific order, as some variables derived from one particular analysis dataset may be used as the inputs to generate other variables in other analysis datasets. For example, the time to event variables in the efficacy and safety analysis datasets are calculated based on the date of the first dose derived in the demographic analysis dataset.
Analysis datasets are generated in sequence
Demographic _______Laboratory __________Efficacy
Vital Sign Safety
Adverse Event
Medications
Source:www.thotwave.com/Document/…/GlobalArch/SUGI117-30_GlobalArchitecture.pdf.

Q-7 What is your involvement while using CDISC standards? What is mean by CDISC where do you use it?
CDISC is nothing but an organization (Clinical Data Interchange Standards Consortium), which implements industrial standards for the pharmaceutical industries to submit the clinical data to FDA.
There are so many advantages of using CDISC standards: Reduced time for regulatory submissions, more efficient regulatory reviews of submission, savings in time and money on data transfers among business.
CDISC standards is used in following activities:
Developing CRTs for submitting them to FDA to get an NDA.
Mapping, pooling and analysis of clinical study data for safety.
Creating the annotated case report form (eCRF) using CDISC-SDTM mapping.
Creating the Analysis Datasets in CDISC and non-CDISC Standards for further SAS
Programming.