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Altrid is a global data analysis partner serving pharmaceutical and biotech clients in the USA and India. We specialize in statistical and clinical programming, CDISC consulting, biostatistics, DMC programming, and flexible partial or full outsourcing. With experience in over 12 global studies across 9 therapeutic areas, we deliver precise clinical data analyses and regulatory submission packages. Our deep regulatory knowledge and robust processes ensure compliant, efficient solutions that accelerate drug development and protect data integrity.

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Biostatistics Consulting Services by Altrid | Pharma & Biotech

Altrid Analysis provides expert Biostatistics Consulting Services for clinical trials, supporting study design, sample-size determination, selection and application of statistical methods, and interpretation of results. Our experienced statisticians collaborate throughout the study lifecycle to ensure rigorous methodology, reproducible analyses, clear reporting, and timely delivery for regulatory submissions and strategic decision-making. Tailored support to meet your study objectives.

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Altrid’s CDISC Implementation and Data Standards Consulting ensures accurate SDTM mapping and ADaM Programming for Pharma & Biotech in the U

CDISC Consulting & Data Analysis Services | Altrid Analysis

Altrid Analysis delivers expert CDISC consulting and data analysis services in India, supporting pharma, biotech, and healthcare companies with compliance and efficiency. Our specialists provide SDTM and ADaM programming, regulatory submission support, workflow optimisation, and biometrics outsourcing. With proven expertise, we ensure reliable, cost-effective, and tailored solutions for every project need.

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Therapeutic Area Standards

Therapeutic Area Standards: Are We Ready for TA-Specific Automation?

Explore how CDISC Therapeutic Area Standards and smart automation can streamline clinical trials while ensuring compliance and data quality.

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Why Working with a Focused CRO Might Be the Best Decision for Your Clinical Trial

Choosing the right Clinical Research Organisation (CRO) is a big decision for any pharmaceutical or biotech company. A CRO becomes your partner through critical phases of drug development—handling everything from data analysis to regulatory submissions.

While full-service CROs offer a wide range of services under one roof, more and more companies are discovering the benefits of working with a focused CRO, also known as a boutique CRO.

So, what’s the difference? And why might a focused CRO be a better fit for your project? Let’s break it down.

What Is a Focused CRO?

A focused CRO specialises in specific services—such as data management, statistical programming, biostatistics, and regulatory data preparation. These are companies that don’t try to do everything, but what they do, they do extremely well.

Think of it like hiring a specialist rather than a generalist. You go to a heart surgeon for heart surgery, not a general doctor. In the same way, a focused CRO provides deep expertise in high-impact areas of clinical trials.

How Is It Different from a Full-Service CRO?

A full-service CRO offers everything from site selection and monitoring to pharmacovigilance, data collection, and submissions. They’re large, structured, and built to run entire trials from start to finish.

A focused CRO, by contrast, is more streamlined. They may not run the entire trial, but they can provide high-quality, highly efficient support in specific areas like:

Statistical & clinical programming

CDISC standards and submission datasets

Biostatistical analysis

Data monitoring and reporting

Focused CROs often work alongside full-service CROs or sponsor teams as part of a blended model.

5 Reasons Sponsors Choose Focused CROs

Here’s why many sponsors are turning to boutique CROs:

1. Expertise That Runs Deep

Focused CROs are specialists. Their teams are built around professionals with years of experience in a particular field. For example, at Altrid, our core focus is clinical programming, data standards (like CDISC), and statistical services.

This means you get:

Higher quality output

Fewer delays or rework

Teams that stay up-to-date on the latest guidelines

2. Faster Turnaround Times

Because focused CROs aren’t managing dozens of services or large trial portfolios, they can often deliver work more quickly and efficiently. There’s less red tape, faster communication, and fewer layers between you and the people doing the work.

In short, your project moves faster.

3. Personalised Service

With a focused CRO, you’re not just a project number. Smaller teams mean:

More direct access to experts

Better collaboration

Greater accountability

Clients often describe the relationship as more like an extension of their own team.

4. Cost-Effective Scalability

Full-service CROs often come with higher overhead. Focused CROs operate leaner, and that means better value. You get expert-level service without paying for unnecessary extras.

Plus, you can scale as needed—adding specialised support only when your project requires it.

5. Flexible Collaboration

Focused CROs can work in a variety of ways:

As your primary partner for key services

Alongside a full-service CRO for specialised tasks

Or to rescue or supplement a project that needs extra support

This flexibility is ideal for small and mid-size sponsors—or anyone who values control, speed, and quality.

A Smart Strategic Choice

Working with a boutique CRO isn’t about doing less—it’s about doing what matters most, better.

In fact, many successful clinical development teams now use a hybrid approach: pairing a full-service CRO with a focused CRO for key areas like data analysis and submission preparation. This allows them to combine the best of both worlds:

The scale of a large CRO

The precision of a specialist

And the speed and flexibility of a boutique partner

Final Thoughts

Clinical trials are complex, and getting them right requires more than just a big team—it takes the right team.

If your project depends on high-quality data, regulatory-ready deliverables, and close collaboration, a focused CRO may be exactly what you need.

At Altrid, we specialise in helping pharma and biotech companies move faster and smarter through key stages of development—without sacrificing quality or compliance. Interested in working with a focused CRO that puts quality and efficiency first? Let’s connect and talk about how Altrid can support your success.

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Statistical & Clinical Programming

Altrid’s Statistical & Clinical Programming delivers machine-readable SDTM & ADaM specs, and automated Quality Control for compliant trial s

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Is your SDTM review systematic and methodological?

In the realm of complex, varied and multi-origin raw datasets, the development of SDTM datasets and related documentation is becoming lengthy process. It requires programmers to refer several different documents such as Codelist, agency guidelines, therapeutic area user guides, Implementation guides along with study documents such as Protocol and CRF completion guidelines. It is, therefore, important to ensure every SDTM datasets and documents are reviewed thoroughly before including in regulatory submission package. This article depicts systematic approach and methodological way of reviewing SDTM datasets, aCRF, define and reviewer’s guide so that submission package is compliant with CDISC guidelines and agency expectations.

The review of SDTM documents and their data do not just start with programming activities, but rather much before. It has been evident that early decision making in deciding which versions of CDISC standard document to choose helps massively and saves significant time. Decision should also be made on several other documents such as QRS, TAUG and any applicable agency guidance.

Usually, organizations do expect their SDTM expert to do heavy lifting of review which ideally should be the case.! However, manual review of aCRF, datasets, specifications, define and csdrg usually takes much time. Moreover, there is always a human error factor to miss out on several review points and it is difficult to verify synchronization between documents & data. To avoid trivial errors, gaps and shortcomings in review, a methodological review should be performed to ensure that the submission package has been prepared with utmost quality.

One of the first suggestions is to build several checklists of aCRF, datasets, define and csdrg review. Furthermore, a well-organized, well-structure specification has been established, which can be verified manually and programmatically to eliminate trivial errors and gaps. This well defined specification can also be source of datasets & define metadata. The pre-defined checks can remove onus from reviewer at significant extent and therefore review can be focused on proper mapping, study specific derivations and making overall package fully compliant.

Below process steps will explain how and what time review should be done. 1. Before programming conduct:

Initial aCRF review: Usually in study, aCRF is first programming document that gets drafted. The way to achieve systematic review of aCRF just does not start once it is completed but rather much before when it is being drafted. It is important in the first place that aCRF is with good quality and generated with proper guidance which aligns with MSG V2.0. Moreover, all agency requirements are also fulfilled. CRF annotations in the form of .xfdf file format can be handy to perform certain checks with specification once it has been drafted. This systematic approach can help cross verify page-numbers & variable existence between aCRF and specification. All necessary decisions on versions should be made before aCRF creation and reviewer must check this against IG, CT version, any TAUG and agency guidance.

2. Review of SDTM Specification: Similarly, as aCRF, to achieve methodological review of SDTM start from specifications. It is important that SDTM specifications are built structurally, so that they can be used to create datasets and define.xml and remain single source of truth. Having well-structured specifications also allows to perform several trivial programmatic checks and eliminates lots of inconsistencies before even actual review starts. Reviewers can then focus on actual mapping instructions, VLM entries and making sure that information in specification has been appropriately filled to avoid conformance issues before even occurring. These focus aspect of specification review can save time and effort to make datasets and entire package compliant with minimal efforts.

3. Review of define & csdrg with data: To reduce efforts in making datasets compliant and re-work at downstream programming, it has been recommended that define.xml must be generated before programming of datasets and thoroughly reviewed without xpt file. This helps to verify specification metadata and allows to have greater synchronization between datasets and define.xml. Leveraging pre-built programmatic checks can eliminates lots of inconsistencies and reduce efforts in trivial review. Reviewers then can focus variable derivations, VLM entries, subset of codelist and overall compliance with define standards. Once define is reviewed and finalized, csdrg should be drafted leaving few sections which are dataset dependent. It is well-observed that 60% of csdrg can be ready even before dataset programming initiation and this approach helps to achieve consistency amongst specification & define from start.

During Programming Conduct:

1. Review of Conformance Report: To reduce time, it is important that conformance reports must be reviewed thoroughly during and after dataset validation. Having performed conformance report review simultaneously during dataset programming conduct versus after full validation of data impacts only one side of programming which significantly saves time and effort. Moreover, this approach avoids any amazement at last stage of programming conduct.

2. Specification Review: During programming conduct, any major updates in specification must be reviewed thoroughly by experienced reviewer. This helps to ensure that updates are aligned with implementation assumption and regulatory agency expectation. Moreover, review must also be focused on promoting consistency across aCRF, dataset, define and csdrg documents so they are prepared without having to wait post programming conduct.

After Programming Conduct:

1. Thorough Review of SDTM Datasets: In several organization, there is a practice to perform review on datasets only once they are fully validated. As depicted in earlier in this article, it is important that systematic reviews should occur throughout the study life cycle. This process helps to eliminate any gaps in documents and/or datasets. However, regardless earlier reviews were taken place or not, once all datasets have been validated, a thorough review on datasets and its conformance report must take place. The review must focus on variable derivation, visit mapping and epoch creation algorithms, key safety and efficacy dataset review. Moreover, appropriate pre-defined programming checks should also be run to ensure datasets follow internal guidance (if any!)

2. Thorough Review of define: Once datasets have been reviewed in detail and updated, a detail review on define must be done along with its conformance report with and without data. Review must focus on VLM, formats, codelist, active linkage with aCRF and csdrg. Moreover, it should also ensure all unresolved issues are explained properly in report to transfer to csdrg at a later stage.

3. Thorough Review of csdrg: In several organization, csdrg is the last document that gets drafted and reviewed. However, having it created before programming or during programming eliminates burden of finalizing it later and reduces the iteration of review. The review must focus on all necessary information starting from correct versions of standards to all the way documenting explanation on conformance issues. Additionally, all lengthy, special and complex programming notes which can help agency reviewer to review must be thoroughly reviewed. Lastly, reviewer must ensure that pdf document follows all FDA pdf rules to comply with submission package.

Conclusion

As depicted throughout in this article, SDTM review is no single time-point bound process, but multi time-point. Once documents are initially reviewed and approved, they serve robust documentation for programming which is highly time-consuming. A methodological and systematic review isn’t just achieved by experienced reviewer but should be done alongside selecting right workflow, well structured documents, well defined internal standards & guidance and usage of internal automation.

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How Altrid Powers Faster Clinical Submissions with Biostatistics & CDISC Expertise

Altrid is a global Contract Research Organization (CRO) trusted by pharma and biotech companies for biostatistics, clinical programming, and CDISC consulting.

We help streamline the path to regulatory submission with:

Experienced statistical programming teams (9+ years avg. experience)

Full CDISC compliance (SDTM, ADaM, define.xml)

End-to-end clinical trial data solutions

➡️ Learn more at Altrid.com