Clinical Analyst

Spatial Front•Washington DC, WA

About The Position

Spatial Front, Inc. (SFI) is seeking a Clinical Analyst to provide scientific and clinical analytical support to a client's multidisciplinary review teams. The role supports regulatory review through evaluation of drug applications, review of clinical safety data, labeling assessment, and preparation of scientific reports. It requires advanced knowledge of health and data sciences and the ability to apply scientific expertise to risk determinations. The Clinical Analyst analyzes submitted data from applicants seeking permission to market new drugs and prepares summaries assessing the adequacy of safety data. The analyst reviews NDAs, BLAs, supplements, and amendments; drafts analytical reports and recommendations for FDA reviewer consideration; and contributes clinical safety review summaries to integrated multidisciplinary assessments. The role also supports labeling review, scientific correspondence, literature review, knowledge management, and preparation for meetings with drug company representatives, advisory committees, and external scientific bodies. This is a full-time W2 position. Candidates must be a U.S. citizen and/or current Green Card holder to meet clearance requirements and will be subject to a background check. Public Trust investigations may take approximately four to eight weeks and require fingerprinting. The stated annual salary is $90,000–$130,000.

Requirements

  • PhD or PharmD required.
  • At least 5 years of experience in a similar role.
  • Expert-level R programming skills.
  • Experience applying clinical safety data analytical skills, including synthesizing clinical and scientific evidence to inform risk assessments.
  • Experience with CDISC data standards, including SDTM and ADaM, and their application to organizing and analyzing clinical trial datasets.
  • Experience producing a variety of written scientific reports and documents.
  • Must be a U.S. citizen and/or current Green Card holder to meet clearance requirements.

Nice To Haves

  • Familiarity with FDA regulations, policies, and procedures concerning safe drugs and biologics, including NDA and BLA review processes.
  • Statistical background, including experience with biostatistical methods commonly used in clinical trial design, analysis, and interpretation, such as survival analysis, mixed-effects models, and hypothesis testing.
  • Machine learning and AI background, including familiarity with predictive modeling techniques.
  • Epidemiological background, including experience with observational study design, real-world evidence, pharmacoepidemiology, or population-level safety surveillance methods.

Responsibilities

  • Analyze and evaluate data submitted by applicants seeking permission to market new drugs, and prepare analytical summaries on the adequacy of the submitted safety data.
  • Review NDAs, BLAs, supplements, and amendments; prepare draft analytical reports and recommendations for FDA reviewer consideration.
  • Incorporate clinical safety data review summaries into integrated multidisciplinary assessments.
  • Assist in reviewing proposed drug labeling to assess whether safety claims are truthful and adequately supported.
  • Provide draft safety data analyses on labeling accuracy and completeness for FDA staff review.
  • Draft scientifically sufficient reports that clearly communicate clinical safety analyses and conclusions.
  • Prepare draft correspondence identifying facts and information inadequately presented in sponsor submissions for FDA reviewer finalization and issuance.
  • Prepare clear summaries of clinical safety data tables, figures, and listings for FDA review teams.
  • Review scientific literature and maintain awareness of current clinical developments and evolving findings in relevant therapeutic areas.
  • Support preparation of background materials for seminars, conferences, and industry meetings.
  • Support clinical review teams preparing for meetings with drug company representatives, advisory committees, and external scientific bodies.
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