FOR BIOTECH TEAMS

Understand your study evidence and data more clearly.

Therapeutics Data helps biotech teams analyze scientific evidence, study the clinical and competitive landscape, review study data and reports, and prepare scientific documentation.

You can start with a single question, a report, or a specific file. No need to roll out a platform or kick off a months-long project.

See services

Defined projects. Clear deliverables. Scientific and analytical work reviewed by people.

FROM INFORMATION TO CLEARER ANSWERS
Therapeutics Data

Pick a source or an answer to see the detail.

Defined projects

Every engagement starts with a clear scope and deliverable, not an open-ended subscription.

Human review

Technology speeds up the work; a person reviews every analysis before it's delivered.

No platform to roll out

Start with a question, a report, or a file. No need to adopt a new system.

The problem

When evidence, data, and reports are scattered, keeping a clear view takes too much time.

A biotech company may need to review publications, understand what other programs are doing, prepare a clinical trial, interpret provider reports, and analyze new data deliveries — often at the same time.

Therapeutics Data takes concrete problems and turns them into defined engagements that add capacity without requiring the team to roll out a new platform or immediately grow its internal structure.

Scattered evidence

Publications, trials, and provider reports live in different places, and someone has to go through them one by one.

Manual review

The team ends up combining searches, files, and spreadsheets to answer questions that should be quick.

Little internal time

Researching, analyzing, and following up on all of it competes with the team's other scientific and clinical work.

SERVICES

Three areas where we can help your team.

Pick the area closest to the problem you have today. Every project is scoped before we start.

Clinical Trial Intelligence

Study preparation and oversight

Get a clearer read on the trial environment, its indicators, and the information you receive from providers.

  • Feasibility and recruitment
  • KPIs and study data
  • CRO reporting

Also available as ongoing tracking.

View clinical study support
Data & Documentation

Analysis and scientific documentation

Review data, analyze results, and prepare scientific documentation with a clear, traceable process.

  • Data deliveries
  • Preclinical data
  • Scientific documentation
View analysis and documentation

Each service's scope is defined with you before any data or document is shared.

AN EASY WAY TO START

You don't need to commission a big project to work with us.

Many engagements can start with a single question, a report, a set of publications, or a data delivery.

You have a scientific question.

You share the topic you need researched.

You get
  • Relevant evidence
  • Key studies
  • Limitations
  • Competitors and references
You need to understand what's happening in an indication.

You share the indication or therapeutic area you're interested in.

You get
  • Active studies
  • Competitors
  • Phases and populations
  • Relevant endpoints and trends
You have your CRO's latest report.

You share the document you just received.

You get
  • Key KPIs (key performance indicators)
  • Changes
  • Points worth flagging
  • Questions for the next meeting
You just received a new file.

You share the file exactly as you received it.

You get
  • Structure check
  • Duplicates
  • Missing values
  • Changes and possible inconsistencies
STUDY KPIs

Clear indicators, transparent calculations.

Each KPI has a definition, a source, and a clear calculation rule so the team can understand what's changing and how to interpret the result.

TD-101Phase II StudyData cut: Aug 28, 2026Synthetic demo data

Forms completed

94%
940 of 1,000 expected forms
↑ 2.1 pts

Share of expected forms that are already complete.

Queries >14 days

39
queries still open
↑ 4

Queries that have been open for more than 14 days.

Median lag

2.4 days
↑ 0.6 days

Typical time between a visit and its data entry.

Discrepancies

2.0%
8 of 400 records compared

Records that should match between two sources but don't.

How are these indicators calculated?
Forms completed
What it measures

The percentage of forms that should be available by a given date and are already complete.

Calculation
forms complete ÷ forms expected × 100
Example
940 ÷ 1,000 × 100 = 94%
Queries >14 days

data query: A data query is a formal question raised when a data point is missing, looks inconsistent, or needs clarification.

What it measures

How many queries remain open more than 14 days after they were created.

Calculation
cutoff date − creation date

If it exceeds 14 days, it's included in the indicator.

To compare sites:
queries open >14 days ÷ forms evaluated × 100
Median lag
What it measures

How long it typically takes between a participant's visit and the corresponding data being entered.

Calculation
Median number of days between the visit date and the first matching entry.

We use the median because it better represents typical behavior when a few cases have extreme delays.

Discrepancies
What it measures

Records that should match between two sources — for example, lab and clinical database — but show differences that need review.

Calculation
records with open discrepancies ÷ records compared × 100
SAMPLE DELIVERABLE

From a dataset to a concrete question the team can review.

This example uses synthetic data — created purely for demonstration — and shows how we can summarize study KPIs, compare sites, review providers, and flag changes that need attention.

TD-101Phase II Study
Synthetic demo data
Data cut: Aug 28, 2026
Expected forms completed
94%
+2.1 pts vs. previous cut
Open data queries >14 days
39
4 new since the last cut
Sites with priority findings
4
2 with high-priority items
Deliveries received on time
75%
1 provider with a late delivery

Sites with the most queries open >14 days

Absolute count and rate per 100 expected forms

Needs reviewWithin expected range
Site 03143.8/100
Site 07125.1/100
Site 1182.4/100
Site 0231.0/100
Site 0921.3/100

Flagged for review = ≥10 queries open >14 days, or a high rate relative to the site's volume.

Open queries >14 days, 12-week trend

010203040W1W6W12WeekOpen queries
39currently+4 vs. previous cut

PRIORITY FINDINGS

Participant 045 — lab date doesn't match the clinical databaseHigh
Site 03 — 12 expected forms outstandingMedium
Site 11 — assessment date recorded before the visitMedium
Site 02 — pending reconciliation with an external fileLow
Site 11 — data query open for 21 days without a responseHigh

Demo priorities represent data review priority, not medical severity.

How we interpret the indicators
Expected forms completed
What it measures
What percentage of the forms that should exist as of the data cut are already complete.
How it's calculated
Forms complete ÷ forms expected × 100, counting participants and visits that occurred up to the cut.
Where it comes from
The study's primary data capture system.
How to interpret it
A low value can indicate an entry lag, not necessarily a problem with the participant.
Open data queries >14 days
What it measures
How many data queries remain open more than 14 days after they were created.
How it's calculated
Queries where cutoff date minus creation date exceeds 14 days are counted.
Where it comes from
The data query log from the clinical system and from providers.
How to interpret it
A sustained increase often signals that a site or provider needs extra support resolving items.
Entry lag
What it measures
How long it typically takes between a visit and the corresponding data being entered.
How it's calculated
Median number of days between the visit date and the first recorded entry.
Where it comes from
Visit and entry dates from the clinical system.
How to interpret it
We use the median, not the average, because it better represents the site's typical behavior.
Cross-source discrepancy
What it measures
Differences between two sources that should match and don't.
How it's calculated
Records with open discrepancies ÷ records compared × 100.
Where it comes from
Comparison between the clinical system and an external source, such as the lab.
How to interpret it
It doesn't indicate which source is correct — only that there's a difference someone needs to review.
Rate per 100 forms evaluated
What it measures
A way to compare sites with different participant volumes.
How it's calculated
Queries open >14 days ÷ forms evaluated × 100.
Where it comes from
The same data used for the open-queries indicator.
How to interpret it
It lets you compare a small site with a large one without size distorting the comparison.

From indicator to a concrete question

Site 07

Queries open for more than 14 days increased since the last cut. Is there a plan to bring this backlog down?

Site 03

Typical data entry lag increased from 1.8 to 4.2 days. Was there an operational change that explains it?

Laboratory

Five records are still pending reconciliation with the clinical database. When are they expected to be resolved?

Reconcile: To reconcile means comparing two sources that should contain compatible information and resolving the differences.

SCIENTIFIC ANALYSIS EXAMPLE

A question can become a structured map of the evidence.

Illustrative example

Question

What clinical evidence exists for a given therapeutic pathway in an indication?

27
relevant publications
12
trials identified
5
active clinical programs
3
main endpoint types

What looks consistent

  • Several studies agree on the size of the effect observed in the main population.
  • The pathway shows a similar safety profile across the identified programs.

What remains uncertain

  • It's unclear whether the effect holds in populations with relevant comorbidities.
  • Long-term follow-up data is still limited.

Studies worth reviewing

  • A Phase II trial with the design most comparable to your own program.
  • A recent systematic review on the same therapeutic pathway.

The numbers and conclusions in this example are illustrative. They don't represent a real analysis or real companies.

How we work

From a concrete question to a useful deliverable.

01

You tell us what you need to solve

It can be a scientific question, a report, a protocol, or a data file.

02

We scope the work

We agree on what we'll analyze, what information we need, and what you'll receive.

03

We research and analyze

We combine scientific review, data analysis, and tools we've built in-house.

04

You get a result you can review

We deliver conclusions, supporting data, references, and the relevant limitations.

If the project requires specialized regulatory, statistical, or clinical expertise, we bring in the right professional.

Technology that helps us work faster, human review that delivers with judgment.

Technology

We use automation and artificial intelligence to speed up tasks like search, classification, document comparison, and data control.

Human review

Everything we deliver is reviewed before it reaches the client. Technology helps us work faster — it doesn't replace scientific judgment.

For biotech teams that need extra capacity at specific points in development.

Therapeutics Data can complement scientific, clinical, data, or development teams when they need to research a question, analyze information, prepare a study, or review documentation without taking on a technology transformation project.

Preclinical biotech

Evidence, competitors, data analysis, publications, and preparation for the transition into clinical development.

Teams preparing a clinical study

Clinical landscape, feasibility, recruitment, KPIs, data, and documentation.

Teams with trials underway

Report review, indicator tracking, delivery control, and provider analysis.

HOW WE COMPLEMENT YOUR TEAM

Analysis, documentation, and additional expertise when the project requires it.

We work with a defined scope and adapt the team to the type of project. We can handle scientific analysis, data, and documentation directly, and bring in specialists when a task needs specific expertise.

Scientific writing

We turn results, evidence, and analysis into clear, well-structured scientific materials for review, publication, or internal communication.

  • Manuscripts
  • Scientific abstracts
  • Posters
  • Literature reviews
  • Scientific presentations
  • Technical reports
Discuss a writing project

Regulatory documentation support

We support the scientific and documentary parts of regulatory work through evidence search, synthesis, organization, and review.

  • Evidence search and synthesis
  • Scientific background
  • Tables and summaries
  • Consistency review
  • Version comparison
  • Drafting support
See documentation support

Specialists when the project requires them

Some tasks need specific expertise. In those cases, we can work alongside specialized professionals based on the project's scope.

  • Regulatory affairs
  • Biostatistics
  • Clinical data management
  • Clinical operations
  • Pharmacovigilance
  • Expertise in specific therapeutic areas

We work with a clear scope: Therapeutics Data does not replace a CRO (a contract research organization), the study medical team, or a specialized regulatory function. When a project requires that expertise, we involve appropriately qualified professionals.

RESOURCES

Clinical research and development, explained clearly and practically.

We're building a practical library to help explain how clinical data and evidence are generated, reviewed, and used in biotech.

Coming soon

How to read a clinical trial

What to look at first when you review a published study's results.

Coming soon

What is a CRO

What a contract research organization does within a clinical trial.

Coming soon

What an endpoint actually means

What exactly the measure used to evaluate a study's outcome is.

Coming soon

How to read a study's monthly report

Which sections are worth reviewing first in a periodic study report.

Coming soon

What KPIs a small company should track

Which indicators matter most when the team and the budget are small.

Coming soon

What a data delivery is

What's involved in receiving and validating a new dataset from a provider.

Coming soon

How to evaluate scientific evidence

How to tell solid evidence apart from preliminary evidence.

Coming soon

Preclinical vs. clinical results

What changes between a result obtained in the lab and one obtained in people.

FREQUENTLY ASKED QUESTIONS

What people usually ask before getting started.

We work with biotech companies and teams that need one-off or ongoing support in scientific research, data analysis, clinical studies, or documentation. The size of the organization isn't a requirement.

No. We also work with preclinical companies or those preparing their first study.

No. A contract research organization, known as a CRO, helps carry out various activities within a clinical trial. Therapeutics Data focuses on scientific analysis, data, clinical intelligence, and documentation.

Yes, when it helps get work done more efficiently. Every analysis and document is reviewed before it's sent to the client.

Yes. Many projects are designed to start with a single question, a report, or a specific dataset.

Yes. Our work can complement the information you already receive from your CRO or other providers.

We can support research, analysis, and scientific writing related to regulatory documentation. When the work requires a specialized regulatory decision, we bring in professionals with specific expertise.

TELL US THE PROBLEM

Start with the question that's eating up your team's time today.

It could be an evidence review, a competitive analysis, a CRO report, a data delivery, or a scientific document. Tell us what you need to solve and we'll tell you if we can help and what the scope would look like.

See services