Data Sciences

Rapid access to clinical data and results to accelerate drug development

Data Sciences

You need data rapidly to make crucial decisions during a study. Faster data means we can provide our customers with earlier interim data and interim PK reports for on-study dosing and formulation decisions.

We understand that on-study changes to early phase study designs and dosing are frequent and so our study strategy for study database design and reporting is built around flexibility and rapid implementation. We use eSource data collection procedures in our clinical units and a joint eSource/eCRF database. Data are available in the study database within hours of collection, ready for remote sponsor access.

Our data science experts support studies conducted at our Miami (US) and Nottingham (UK) clinics. With global SOPs, templates, and standards, we also adapt them for use with sponsor templates/standards. Our services are fully integrated, and we assign a single Project Manager for all drug product, clinical and data sciences activities.


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Data Science at Quotient Sciences comprises six specialist departments and over 100 staff:

Data Management and Database Programming

  • Study eSource/eCRF database set-up and maintenance
  • Study database build using Anju’s TrialOne system, a single system for both eSource collection in clinic and as an eCRF for data management. As a result, TrialOne use and Quotient processes reduce data query rates, data transcription and timelines.
  • Data Management Plan, data cleaning, coding, query issue and database lock

Statistics and Statistical Programming

  • Protocol input, sample size calculation and randomization
  • Statistical Analysis Plan and formal statistical analysis/interpretation
  • Program study listings, tables and figures and CDISC datasets (SDTM and ADaM)
  • Define.xml package including Reviewers Guide and all related documentation


  • Rapid interim PK turnaround times for formulation decisions or SAD/MAD safety evaluation
  • PK parameter estimation using Phoenix WinNonlin and interpretation
  • Modeling and simulation using GastroPlus, including development of IVIVCs

Medical writing

  • Protocol writing
  • Clinical study report according to FDA guidance for industry and related submissions using eCTD specification

Standardizing study data with CDISC

When you need compliant datasets, enlist experts that understand CDISC’s impact on early phase studies and its importance to your future regulatory submission. As a CDISC Gold Member, we have built CDISC standards into all our data management and statistical procedures for over 400 early phase studies. We also use the same software as FDA for dataset validation (Pinnacle21 Enterprise edition) and to aid define-xml package generation. Our experts:

  • Develop dataset specifications and an aCRF with reference to SDTM and ADaM implementation guides

  • Program SDTM and ADaM datasets according to specifications, including verification, quality control and validation

  • Provide metadata files and blankcrf.pdf

  • Include all clinical, pharmacokinetic, pharmacodynamic and scintigraphic data

  • We also offer full define.xml package including define.pdf, trial design datasets, subject-level datasets, traceability documentation and data reviewer’s guides

An example of how a drug travels through the nasal pathway and is dispersed in the lungs through the use of scintigraphy

Statistics, Pharmacokinetics and Scintigraphy

Our statistical, pharmacokinetic and scintigraphic experts understand clinical pharmacology studies and their specialized challenges. Optimize your study objectives, design and subject numbers, and maximize your use of study data:

  • Access input into clinical protocols and designs and ensure all output complies with the ICH, CHMP and FDA

  • Provide data analysis and interpretation, such as interim assessments to assist you with real-time decision making

  • Leverage expert review and interpretation of scintigraphic data, including qualitative and quantitative analysis of drug product performance and pharmacodynamic effects during your study


Learn more about Data Sciences at Quotient