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Trusted by teams at leading life sciences companies.

8 out of the top 20 pharma companies use Cellbyte,
and 97% of our users recommend it.*

* User survey, July/August 2026

Bayer Genmab Kyowa Kirin Chiesi
…and many more
…and many more

Hear it from our customers

“Cellbyte consolidates complex HTA data in a structured way, enabling users to find insights in just a few clicks. Its AI analyzes multiple analogs simultaneously, examining study designs, outcomes, and rationales, which can now be completed in few minutes instead of hours. The platform also ensures reliability by linking each insight directly to its original source. ”

Gustavo Agreda Duffaut
Global Market Access Manager, Oncology Pipeline, Bayer AG
Bayer

“HAS documentation used to mean reading TC opinions and hearing transcripts line by line. With Cellbyte I can interrogate them directly - surfacing the committee's reasoning, the questions raised in the hearing, and how they shaped the final rating, with every point traceable to the original text.”

Valentin Debarge
Market Access, Pricing & Public Affairs Director, Genmab
Genmab
Customer quotes
“The column creator is the feature I use the most.” “I could just filter, and it took maybe ten minutes.” “You can go directly to the place where it took the information.” “EMA information and price information all in one. Very fast.” “It draws on specific sources – you can trust it a lot more.” “It saves a lot of time.” “You can create your own platform for your specific needs.” “I don’t think I’ll ever have to go into the EMA website again.” “There is no reservation for me to not recommend this.” “Per request I easily saved 90 minutes to two hours.” “Information always has references – that is really good, so that I can click into it and see.” “The column creator is the feature I use the most.” “I could just filter, and it took maybe ten minutes.” “You can go directly to the place where it took the information.” “EMA information and price information all in one. Very fast.” “It draws on specific sources – you can trust it a lot more.” “It saves a lot of time.” “You can create your own platform for your specific needs.” “I don’t think I’ll ever have to go into the EMA website again.” “There is no reservation for me to not recommend this.” “Per request I easily saved 90 minutes to two hours.” “Information always has references – that is really good, so that I can click into it and see.”
Customer case study · Lilly Deutschland · Oncology

Assessing the impact of
biomarker status on benefit
ratings and evidence confirmation

Challenge

Assess whether biomarker-based oncology therapies are rated differently by the G-BA, and whether orphan status offsets the difference. No database classifies AMNOG procedures by biomarker status - by hand, a 8-week manual extraction across 521 procedures.

What Cellbyte did

Cellbyte classified every G-BA oncology assessment by biomarker status from its indication wording. It merged benefit rating and orphan designation onto each procedure, with passage-level citations.

From each procedure’s documents, it also extracted whether the manufacturer’s evidence was judged sufficient to support the benefit rating. It then mapped these classifications to negotiated prices and patient populations to size the financial impact of biomarker status.

Outcome

8 weeks → 2 weeks

15 years of G-BA oncology decisions across four research questions, delivered as a sourced deck in two weeks.
97% less research time.
ISPOR Europe 2026 Presenter
Published at ISPOR Europe 2026
Abstract ↗
Deliverable excerpt · benefit-rating mix by biomarker status
Biomarker therapies land at the extremes: more top ratings, more no-benefit decisions.
% of each biomarker group’s assessments
0% 10% 20% 30% 40% 50%
2.9%
0.7%
24.5%
22.2%
13.5%
20.4%
16.5%
19.0%
42.2%
36.6%
Awarded 4.2× more often
with a biomarker
Major
Considerable
Minor
Non-quantifiable
No added
benefit
G-BA added-benefit rating
Biomarker-based (n=237) No biomarker (n=284)
n=521 (G-BA oncology, 2011–Jun 2026) · Lesser benefit and Not proven (n=4) omittedCellbyte · G-BA decisions
ISPOR Europe 2026 Presenter
Published at ISPOR Europe 2026
View abstract ↗
Customer case study · Top-20 pharma · Oncology

Assessing the impact of OS length on benefit rating and pricing outcomes

Challenge

Assess how the OS delta between an assessed product and its trial comparator affects benefit rating and price. Previously, answering took a three-week analyst sprint through 150+ page documents.

What Cellbyte did

Cellbyte surfaced every G-BA oncology assessment with each product's benefit rating and launch price. It extracted the OS difference from each dossier, with passage-level citations.

Outcome

3 weeks → 8 hours

A decade of OS deltas, mapped to ratings and negotiated prices, delivered as a referenced Excel in a single working day. 93% less research time.

Deliverable excerpt · benefit-rating mix by OS gain
Longer overall-survival gains map to stronger G-BA benefit ratings.
100%75%50%25%0%
No robust
OS gain
n=354 · 73%
Small
>0–90 d
n=19 · 4%
Moderate
>90–180 d
n=40 · 8%
Substantial
>180–365 d
n=44 · 9%
Very large
>365 d
n=25 · 5%
Major Considerable Minor Non-quantifiable No added benefit Not proven Lesser benefit Missing
% of each OS category’s assessments · n=482 total (G-BA oncology)Cellbyte · G-BA decisions
“Cellbyte saved me so much time. I can quickly check the sources and the specific passage where the AI found certain information.”
Senior Manager, Global Pricing & Market Access · Top-20 Pharma

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