SmartAnalyst “Value Evidence” Proposition – Seamlessly integrated with domain expertise and analytical skills. Over 198 projects and 100+ publications completed in the last 5 years across therapeutic areas and type of projects.

 

  • Experience: Extensive experience in RWE studies and pharmacoeconomic models, in-depth experience in oncology, immunology and CVM, stable and long-serving study team
  • Flexibility: Allow customizability in study design, align pace with study team, and accommodate midcourse corrections
  • Responsiveness: Timely delivery and consistently able to attend to urgent requirements

 

 

What HEOR Solutions We Provide:

  • Evidence Generation
    • Literature Reviews Both targeted as well as systematic literature reviews conducted either as independent studies or as part of evidence generation for health economic models use of databases (e.g. Optum Integrated, IBM/Truven, IBM Watson Explorys, MarketScan, SEER-Medicare, and IQVIA Pharmetrics)
  • Modeling
    • Survival modeling and extrapolations
    • Pair wise meta-analysis – random/fixed effects, frequentist/Bayesian
    • Network meta-analysis and indirect treatment comparison
    • Population adjusted indirect comparisons – MAIC, STC, prognostic modeling
  • Clinical Trial Analysis
    • Clinical effectiveness – PFS, OS, TTP, DoR, TFS, TTD
    • Healthcare resource utilization (HRU)
    • Cost analysis based on HRU
  • Pharmacoeconomic Modelling
    • Cost-effectiveness – both for internal assessments and submission-ready
    • Budget impact
    • Cost minimization
    • Cost comparison using clinical trial data
  • Infectious Disease
    • Simulating epidemics/outbreaks (e.g. Ebola)
    • Impact of vaccination on outbreaks
    • Estimating course of perennial conditions (e.g. Tuberculosis, HIV)
    • Impact of treatments
  • Dynamic Disease Models for Oncology
    • Estimation of treatment starts, prevalence in micro-settings within indication (e.g. size of opportunity in third line for “fit” patients who have failed regimens x and y)
    • Take into account survival curves to progress patients from one line to the next, while keeping treatment history in mind
    • Relevant patient segmentation for indication built in (e.g. cytogenetic mutation, age, fitness, and relapsed)
    • Have ready models for 13 oncology indications
Examples of Modelling Studies Conducted in the Recent Past
Clinical effectiveness and cost-effectiveness analysis for a new intervention in relapsed/refractory multiple myeloma for submission to NICE (UK)
Budget impact modeling for a new intervention in relapsed/refractory multiple myeloma
Comparative effectiveness, cost effectiveness and budget impact analyses for a new intervention in an endocrinology disorder for an HTA submission in Mexico
An early cost-effectiveness model for a upcoming drug in heart failure patients
Microsimulation modeling to assess cost-effectiveness and budget impact of a pipeline asset in atopic dermatitis
Adapting the global cost-effectiveness and budget impact model for a heme-oncology asset for country affiliates
Cost comparison analysis in RCC using real-world and clinical trial data
Modeling cost-effectiveness analysis of treating latent tuberculosis in Thailand
Evaluation of vaccination strategies on the epidemiology of Ebola, using a mean-field compartmental model in MATLAB/R, and determining the cost-effectiveness of such strategies