Overview
At the core we are a statistical company. Our expertise is in Statistics as it is applied to all phases of drug development. We do it deliberately, efficiently, and with passion. We focus on current regulatory frameworks, innovative designs and analytical methods. Our services span from consulting, developing statistical plans, conducting data analysis, and collaborating with the sponsor to prepare for regulatory submissions. Our other services, such as Data Management, are also informed and enhanced by our statistical outlook.
- Statistical Consulting – At the project level we can assist you in preparing a Clinical Development Plan. At the individual protocol level we can help you prepare a protocol by translating the objectives into testable hypotheses, and choosing the proper study design and analytical strategies. Our value proposition is not just in the statistical know-how, but in how we apply this knowledge in the context of regulatory expectations. We write the Statistical Analysis Plans (SAP) in great detail and well before the database-lock so that these expectations are met without issues.
- Clinical Study Report (CSR) – Since we often start at the protocol stage or earlier, and generate the statistical outputs ourselves, we take on the responsibility of reviewing the CSR to make sure that the results are presented accurately and that they lead to appropriate conclusions. We strictly follow the ICH E9 guidance so that the CSR meets the regulators’ expectations.
- Data Monitoring Committee (DMC) – We prepare DMCs by helping draft the Charter, recruiting the voting member statistician in the committee and/or supporting the committee with statistical outputs. We have also participated as a voting member of the safety committees.
- Regulatory Interaction – We are happy to defend the design and the statistical methodology we suggest in the protocol and the SAP to the regulatory bodies. We have had experience in preparing briefing books, providing written responses to the agencies, and also numerous interactions with the agencies in face-to-face meetings.
The following is a list of tasks taken up by our statistics group:
- Consulting on development plans
- Statistical input in protocols, and preparation of statistical section including sample-size detarmination
- Provide expertise on statistical designs including adaptive designs
- Preparation of Statistical Analysis Plans
- Support safety and dose selection committees
- PK data modeling
- Preparation of Clinical Study Reports
- Data Monitoring Committee membership
- Statistical support for Data Monitoring Committees
- Preparation of submission packages including briefing books and story boards
- Regulatory interaction including face-to-face meetings with regulators
- Regulatory filing support including responding to regulatory questions
Good inference can only be based on good data. And collecting good data has to be planned properly and executed without fail. Our clinical data management group provides end-to-end database build and data management services ensuring a clean database. After all, the integrity of the statistical inference rests on the accuracy of the data.
- Study Start – The very first step for us is a thorough review of the protocol before we design the CRFs. We seek statistician’s help in reviewing the subtle aspects so that it is clear what data the analyses will be based on. The database is built in-house with appropriate skip logics and edit checks built in. The study documents such as the DMP, DTs and CCG, are prepared at this stage to lay out the data management plan, handling of the external vendor data and instructions for filling out the CRFs.
- Study Conduct – We clean the data continuously and share progress reports with the sponsor at regular intervals. At this stage most time is spent on generating queries and resolving them with the sites. The data reconciliation test-runs are often conducted with vendor data at this stage.
- Study Close-out – We proactively prepare for the study close-out phase. Final reconciliation of the SAE data and the external laboratory data happens at this time. We use statistical software to address these final reconciliations. We also close out queries, seek finalization of protocol deviation list and prepare documents for signature at this point. Final archival of the database happens after the data base lock, and after the team determines that all issues have been addressed.
These are the tasks performed by our data management group:
- CRF Design
- CRF Completion Guidelines
- Database Development and Deployment [we build study databases using a number of platforms]
- Data Migration
Data Review and Reporting Analytics (JReview, Spotfire, Tableau, etc.)
Produce submission-ready CRFs
- Data Management Plans
- Data Review Plans
- Query Generation and Resolution
- Automated Data Validation to Streamline and Optimize Data Review
- Medical Safety Review Meetings
- Medical Coding
- SAE Reconciliation
- 3rd Party Vendor Data Transfer Specifications and Reconciliation
- Database Lock
- Database archival
Our experienced statistical programmers generate CDISC-compliant datasets (SDTM and ADaM) and statistical outputs (TLFs) that follow the Statistical Analysis Plan. The group is also involved in the preparation of outputs for safety reviews for on-going studies,annual regulatory reports, and preparation of integrated documents for regulatory filing.
- CDISC Standards – Regulatory agencies require that all studies for submission meet the SDTM and ADaM standards. Our programmers have in-depth knowledge of handling any study data and turn them into these standard datasets efficiently. We also prepare documentation for the regulators that show traceability of the data from raw datasets to statistical outputs. Our services include
⨀ Create customized CDISC solutions
⨀ Create CDISC SDTM domains from client-defined data standards
⨀ Ensure compatibility with any version of the SDTM Implementation Guide
⨀ Program SDTM and ADaM datasets from raw data
⨀ Map studies from legacy to CDISC standards for ISS/ISE reporting and FDA submission
⨀ Create Develop Submission-Ready Documents, Packages and Reviewers Guides (DEFINE.XML)
⨀ Create ADaM domains to support TFLs and maintain data traceability from CRF to CSR (mapping documents)
⨀ Provide Centralized Data Storage/Metadata Repository
- Programming of Outputs – Our programming team works closely with the study statisticians. Questions from the protocol and SAP are thoroughly understood before programming of the analysis datasets, tables, listings and figures (TLFs). At Inference all outputs go through a 3-step QC process including double-programming. We ensure that the outputs are based on accurate data derivation, and follow the protocol, SAP, programming specs, and mock shells. The QC ends with a thorough review from the statistician who ensures that the results make sense in the context of the trial.
Epidemiology /Real World Evidence Services in Clinical Development and Outcomes Research
We offer our biotech partners a range of epidemiological services supporting drug development processes, regulatory approval, post-marketing studies and health technology assessment.
We offer our biotech partners a range of epidemiological services supporting drug development processes, regulatory approval, post-marketing studies and health technology assessment.
Deepen Understanding of Patient Populations
- Gain more precise insights into prevalence, incidence, temporal trends, and comorbidities to better define and target patient populations.
Improve Disease Understanding
- Build and leverage natural disease history and progression models, along with prognostic and predictive biomarkers, to inform trial design and therapeutic strategies.
Explore Healthcare Utilization
- Assess unmet medical needs, predict market potential, and evaluate the patterns of concomitant medication use.
- Identify at-risk populations for monitoring and develop robust statistical models that provide context on the current treatment landscape and demonstrate the public health impact of new therapies for regulatory submissions.
Post-Marketing Insights
- Design post-marketing studies and conduct health technology assessments, including indirect treatment comparisons such as matching-adjusted indirect comparisons (MAIC) and simulated treatment comparisons (STC); compare efficacy of your medication with that of competitors to demonstrate value to health technology assessment regulators.
Causal Inference with Observational Data
- Apply advanced causal inference methods like propensity score analysis, expert-driven Directed Acyclic Graphs (DAGs), G-estimation, IP-weighting, marginal structural models, and instrumental variables to analyze observational studies and support your evidence-based decision-making process.
Early phase studies are for learning a new drug’s safety profile, dose, route of administration, dosing frequency to optimize the efficacy potential of the molecule. Pharmacokinetic (PK) data, that is, information on what the body does to the drug, drive key decisions for the development process at this stage. We, at Inference, specialize in these early development studies. These studies require optimal collection of PK data and appropriate modeling for reaching key decisions.
- Protocol Review – We can provide both strategic and tactical suggestions on the PK section of the protocol. The collection of PK data, for plasma or urine or both, not only must be such that the trial objectives can be addressed, but also they need to be looked at with a view of the eventual regulatory submission where additional questions about the drug’s absorption, distribution, metabolism and excretion are well documented.
- Non-compartmental Analysis – We have resources with deep experience in PK analysis. Our pharmacokineticist uses WinNonlin to derive the pharmacokinetic parameters according to the methodology specified in the Pharmacokinetics plan or Statistical Analysis Plan (SAP).
- PK/PD Modeling – Often dosing and go/no-go decisions depend on a favorable relationship between clinical outcomes and a compound’s PK profile. We have extensive experience in modeling this relationship – with biomarker, efficacy and safety data.
- POP PK analysis and other Modeling – We also have experience in performing non-linear modeling for Population PK analysis. Our software of choice is Phoenix NLME.
Inference’s medical writers have years of experience in preparing ICH-compliant study documents from protocols to study reports to integrated documents for regulatory submission. They have broad experience in using sponsor’s templates and style guides. And if no sponsor template is available Inference will use its own templates. Our writers work closely with our biostatistics, programming, PK/PD and project management teams to deliver accurate, timely, and cost effective documents to the highest ethical and scientific standards.
- Protocol – Our writers can prepare a detailed protocol by aligning the objectives, study design and methods by using their extensive understanding of the regulatory framework for presenting such information as well the need for scientific clarity in executing the corresponding clinical trial.
- Clinical Study Reports – We have resources with deep experience in the preparation of CSRs, based on the ICH E3 guideline. Our writers work closely with the biostatisticians to make sure the results are presented and interpreted accurately.
- Integrated Summary of Safety/Efficacy – We prepare integrated reports such as efficacy, PK and safety summaries as well as overviews and briefing books for submission to regulators.
- Other Reports – We also write other reports such as Development Plans, Investigative Brochures, Annual Safety Reports etc.