Intelligence for Grants, Not Just Compliance
Intelligence for Grants, Not Just Compliance
What a grants or investigator-initiated study program should be able to tell you about itself, and what to ask a vendor who says their system can.
What a grants or investigator-initiated study program should be able to tell you about itself, and what to ask a vendor who says their system can.
What a grants or investigator-initiated study program should be able to tell you about itself, and what to ask a vendor who says their system can.
By Alyssa Cook | COO and SVP Client Solutions, SteepRock, Inc
By Alyssa Cook | COO and SVP Client Solutions, SteepRock, Inc
October 1, 2026
October 1, 2026
The questions every program manager gets asked and can’t answer quickly
Every grants and investigator-initiated study program I have worked on holds the same records. Requests received. Committees convened. Fair market value assessments. Contracts, milestones, payments, outcomes reports, and the reasons behind every approval and every decline. Some of these programs have been running for more than fifteen years, and the records are deep.
What none of them could do, until recently, was answer a question across those records. The funding history sat in the grants system. The investigator’s publications and trials sat somewhere else. The company’s engagement history with that investigator sat in a third place. When leadership asked which investigators the company had funded in a disease area and how that compared to who was shaping it, the answer took days and arrived as a spreadsheet someone built by hand. It was out of date by the time it was presented.
That has changed. The AI capability we run on our own grants and investigator study systems, SteepRock Embedded Intelligence, reads across the funding record, the investigator profile and the engagement history in one session and produces the answer as a finished report. This article covers the questions that matter, why the compliance floor every vendor offers doesn’t get you there, and what to ask any vendor who says their system does the same thing. If you are being asked to consolidate these programs onto a single suite, the questions at the end are what I would settle before agreeing.
A note on nomenclature
The industry uses several names for the same programs, and the terms can be confusing between companies.
Programs that fund education and activities. Independent medical education (IME) grants, sometimes called continuing medical education (CME) grants, to accredited providers. Charitable donations and corporate giving to patient advocacy groups and foundations. Sponsorships of third-party meetings and conferences. Fellowships that fund postdoctoral research and training.
Programs that fund research. Investigator-initiated studies (IIS), also called investigator-initiated trials (IIT), investigator-sponsored trials (IST) or investigator-initiated research (IIR). The investigator conceives the study, the company funds it, and the investigator is the sponsor under FDA regulations. Company-sponsored real-world evidence and health economics studies often run through the same infrastructure.
On our platform, education programs run through the Educational Grants Solution™ (EGS™), also offered as the Global Grant Solution, and research programs through the Investigator Sponsored Trial Solution™ (ISTS™). Their shared foundation is what makes the questions below answerable, and I will come back to why.
Seven questions that change how a program is run
Program managers know which questions they have never been able to answer quickly. They are the same ones leadership asks at every review and every renewal, and every time the answer has meant a manual compilation.
Who have we funded over time, and how does that map to the expert landscape in the disease area? This is the strategic question. A grants or investigator study program is a map of where the company has placed its research investment across the physicians and institutions that shape how a therapy is studied and understood. Until now that map existed in fragments, assembled by hand for a leadership meeting. It can now be produced from the program’s own records, cross-referenced against the publication, clinical trial, congress, claims and payment data that describes each investigator’s standing in the field.
Figure 1. Where the money went. Each dot is an investigator; the vertical axis is five-year company funding, the horizontal axis is standing in the field. Illustrative example built on synthetic data; no client data is shown.
Where are the gaps between what we have funded and what our strategy calls for? This follows from the first question but is harder to do by hand, because it means comparing the funding record against the medical and commercial priorities. A session can show which therapeutic areas, and research questions have received funding and which have not, and can identify investigators whose work aligns with an unfunded priority.
What has the collective output of funded programs been? When a program comes up for renewal, or leadership asks whether the investment was worth it, the answer lives in the milestones, publications, outcomes reports and close-out summaries the program has collected over its life. Compiling it is the most labor-intensive task of the year for many program managers. The program can now produce it.
How long does a request take from submission to decision, and is that normal? Cycle time is the metric every program manager gets asked about and nobody can benchmark, because no public source tells you whether a thirty-day median is fast or slow for your kind of program. This summer one of our clients received a quarter-to-date grants executive report and a request cycle time analysis for a mid-year leadership review, produced from their own portal data and delivered as a finished presentation [2].
Does this investigator have a conflict? Before funding an investigator, the program needs to know whether that person is also a paid speaker for the company, is receiving funding from another program at the same company, has Open Payments records that would raise a question at audit, or holds a competing commercial relationship. That check means looking across the grants system, the speaker program, the engagement history and the payment data. In most organizations it is done by email. Here it is done in the session, from the same data layer that holds the investigator’s full profile.
Does this budget line exceed fair market value? Every funding request for services is assessed against the program’s fair market value schedule. In most programs the manager pulls the rate table, compares each line, and documents the result. The comparison can now be run in the session, with the lines that exceed the schedule flagged and a record of the check that a reviewer or an auditor can trace.
Did the funded work change anything, and can we show it? This is what leadership means when it asks about return, and it has two different answers depending on the program.
For investigator studies, the return is evidence. Did the funded studies publish, where, and were they cited? Did any reach a guideline, a label change or a follow-on company-sponsored trial? Did the investigators we funded become more active in the disease area afterward, in trials and at congresses, than comparable investigators we did not fund? That last comparison needs the expert data layer, not the grants system, and it is the closest thing to a return calculation these programs can defend.
For education grants the word “return” needs care. The PhRMA Code and the ACCME standards exist to keep grant decisions apart from commercial outcomes, so the answer can never be about prescribing or product. It can be about the gap the activity was funded to close. Accredited providers already report outcomes against Moore’s framework, from participation and satisfaction through learning, competence, performance and patient health, in the close-out reports the program collects. Almost no program reads those reports across a portfolio. Read together, they answer a question a compliance officer will accept: of the forty activities we funded this year, how many reported a measured change in competence or performance, and which gaps are still open.
Figure 1. Where the money went. Each dot is an investigator; the vertical axis is five-year company funding, the horizontal axis is standing in the field. Illustrative example built on synthetic data; no client data is shown.
Where are the gaps between what we have funded and what our strategy calls for? This follows from the first question but is harder to do by hand, because it means comparing the funding record against the medical and commercial priorities. A session can show which therapeutic areas, and research questions have received funding and which have not, and can identify investigators whose work aligns with an unfunded priority.
What has the collective output of funded programs been? When a program comes up for renewal, or leadership asks whether the investment was worth it, the answer lives in the milestones, publications, outcomes reports and close-out summaries the program has collected over its life. Compiling it is the most labor-intensive task of the year for many program managers. The program can now produce it.
How long does a request take from submission to decision, and is that normal? Cycle time is the metric every program manager gets asked about and nobody can benchmark, because no public source tells you whether a thirty-day median is fast or slow for your kind of program. This summer one of our clients received a quarter-to-date grants executive report and a request cycle time analysis for a mid-year leadership review, produced from their own portal data and delivered as a finished presentation [2].
Does this investigator have a conflict? Before funding an investigator, the program needs to know whether that person is also a paid speaker for the company, is receiving funding from another program at the same company, has Open Payments records that would raise a question at audit, or holds a competing commercial relationship. That check means looking across the grants system, the speaker program, the engagement history and the payment data. In most organizations it is done by email. Here it is done in the session, from the same data layer that holds the investigator’s full profile.
Does this budget line exceed fair market value? Every funding request for services is assessed against the program’s fair market value schedule. In most programs the manager pulls the rate table, compares each line, and documents the result. The comparison can now be run in the session, with the lines that exceed the schedule flagged and a record of the check that a reviewer or an auditor can trace.
Did the funded work change anything, and can we show it? This is what leadership means when it asks about return, and it has two different answers depending on the program.
For investigator studies, the return is evidence. Did the funded studies publish, where, and were they cited? Did any reach a guideline, a label change or a follow-on company-sponsored trial? Did the investigators we funded become more active in the disease area afterward, in trials and at congresses, than comparable investigators we did not fund? That last comparison needs the expert data layer, not the grants system, and it is the closest thing to a return calculation these programs can defend.
For education grants the word “return” needs care. The PhRMA Code and the ACCME standards exist to keep grant decisions apart from commercial outcomes, so the answer can never be about prescribing or product. It can be about the gap the activity was funded to close. Accredited providers already report outcomes against Moore’s framework, from participation and satisfaction through learning, competence, performance and patient health, in the close-out reports the program collects. Almost no program reads those reports across a portfolio. Read together, they answer a question a compliance officer will accept: of the forty activities we funded this year, how many reported a measured change in competence or performance, and which gaps are still open.
Figure 1. Where the money went. Each dot is an investigator; the vertical axis is five-year company funding, the horizontal axis is standing in the field. Illustrative example built on synthetic data; no client data is shown.
Where are the gaps between what we have funded and what our strategy calls for? This follows from the first question but is harder to do by hand, because it means comparing the funding record against the medical and commercial priorities. A session can show which therapeutic areas, and research questions have received funding and which have not, and can identify investigators whose work aligns with an unfunded priority.
What has the collective output of funded programs been? When a program comes up for renewal, or leadership asks whether the investment was worth it, the answer lives in the milestones, publications, outcomes reports and close-out summaries the program has collected over its life. Compiling it is the most labor-intensive task of the year for many program managers. The program can now produce it.
How long does a request take from submission to decision, and is that normal? Cycle time is the metric every program manager gets asked about and nobody can benchmark, because no public source tells you whether a thirty-day median is fast or slow for your kind of program. This summer one of our clients received a quarter-to-date grants executive report and a request cycle time analysis for a mid-year leadership review, produced from their own portal data and delivered as a finished presentation [2].
Does this investigator have a conflict? Before funding an investigator, the program needs to know whether that person is also a paid speaker for the company, is receiving funding from another program at the same company, has Open Payments records that would raise a question at audit, or holds a competing commercial relationship. That check means looking across the grants system, the speaker program, the engagement history and the payment data. In most organizations it is done by email. Here it is done in the session, from the same data layer that holds the investigator’s full profile.
Does this budget line exceed fair market value? Every funding request for services is assessed against the program’s fair market value schedule. In most programs the manager pulls the rate table, compares each line, and documents the result. The comparison can now be run in the session, with the lines that exceed the schedule flagged and a record of the check that a reviewer or an auditor can trace.
Did the funded work change anything, and can we show it? This is what leadership means when it asks about return, and it has two different answers depending on the program.
For investigator studies, the return is evidence. Did the funded studies publish, where, and were they cited? Did any reach a guideline, a label change or a follow-on company-sponsored trial? Did the investigators we funded become more active in the disease area afterward, in trials and at congresses, than comparable investigators we did not fund? That last comparison needs the expert data layer, not the grants system, and it is the closest thing to a return calculation these programs can defend.
For education grants the word “return” needs care. The PhRMA Code and the ACCME standards exist to keep grant decisions apart from commercial outcomes, so the answer can never be about prescribing or product. It can be about the gap the activity was funded to close. Accredited providers already report outcomes against Moore’s framework, from participation and satisfaction through learning, competence, performance and patient health, in the close-out reports the program collects. Almost no program reads those reports across a portfolio. Read together, they answer a question a compliance officer will accept: of the forty activities we funded this year, how many reported a measured change in competence or performance, and which gaps are still open.
Figure 2. The same program read for results. Left: evidence produced by funded investigators against a comparable unfunded group. Right: outcomes reported by accredited providers, by Moore level, across a year of funded activities. Illustrative example built on synthetic data; no client data is shown.
These questions work for one reason: the programs, the expert profiles and the engagement history are on the same system, and the AI reads across all of them under the same permission rules that govern who sees what in the program itself. A capability bolted onto a grants system alone can’t answer most of them, because most of the data it needs isn’t there.
Where the reviewer still sits
None of this removes a person from the decision. The AI does not approve a grant, set a fair market value figure or clear a conflict. It produces the analysis and the record behind it, names the sources it drew on, and a reviewer signs off. When something in the record can’t be verified, a fair market value figure, an investigator credential, a prior payment, it should say so and leave the gap visible. We have published an example of ours doing exactly that [3], and I would ask any vendor for the same before believing a demo.
The compliance floor, and why it is the floor
Grants systems generally cover compliance, and for good reason. The obligations are real.
The rules behind that floor are the federal Anti-Kickback Statute and the Office of Inspector General’s compliance guidance for manufacturers [4][6], the Sunshine Act and its Open Payments reporting [7], the PhRMA Code [8], the ACCME Standards for Integrity and Independence [9] and, in Europe, the EFPIA Code [10]. When a company funds an investigator-initiated study, the FDA rules for sponsors and investigators at 21 C.F.R. Part 312 apply as well [11].
Grants systems generally handle request submission, routing, committee review, contracting and payment tracking. That is the floor. What separates a program that can defend itself at audit from one that can’t is the quality of the record behind each decision: who reviewed it, on what basis, against what fair market value standard, with what conflict check, and what the program produced as a result. And what separates a program that runs as an administrative function from one that runs as part of the company’s medical and market development strategy is the ability to ask questions across its own history. The floor doesn’t give you that.
Eight questions to put to any grants or investigator study vendor
These are the questions I would want answered in writing before signing up, and they are the ones we expect to be asked ourselves.
Can your system answer a question that draws on the grants record, the investigator’s profile and the company’s engagement history in a single session, or do I have to export and reconcile?
How does the AI inherit the permission model that separates medical from commercial activity? Can a commercial user, or a commercial-facing agent, see anything about a pending request?
When the AI produces a recommendation on a grant or a study, what in the record shows a reviewer that it was AI-produced, which sources it drew on, and what the reviewer changed?
What does the system do when a fair market value figure, an investigator credential or a prior payment can’t be verified from the record? Show me a published example of it declining to answer.
How many grants and investigator study programs have you administered end to end, from concept through outcomes reporting, over how many years?
Can my administrators change forms, routing rules, reviewer pools and thresholds without a vendor release or a paid project? What happens to my configuration and history at each release?
Can the system show what funded work produced afterward: publications, trials and congress activity for funded investigators against a comparable unfunded group, and provider-reported outcomes by Moore level aggregated across a grants portfolio?
Who owns the program record at the end of the term, in what format does it leave, and how long is it retained after termination?
Who wrote this, and why
I lead operations and client solutions at SteepRock, which means the teams that implement our systems, support our clients day to day, and sit with them while they put the work to use. I joined SteepRock in 2004, and the 2008 investigator-initiated research deployment for a top-ten pharmaceutical company described below was one of my early engagements. I have worked on grants and investigator-initiated study programs continuously since. The questions in this article are the ones I hear from many program managers and compliance officers we work with.
SteepRock has administered these programs continuously since it put a dedicated investigator-initiated research system, with a fully integrated backend database, into production for a top-ten pharmaceutical company in 2008. Those programs run today through EGS and ISTS on a single-tenant, backward-compatible platform that has carried client configurations forward across every release. Since 2025 the finished reporting these programs need has been produced by SteepRock Embedded Intelligence and included in the license, with no charge by the document or by the question.
Figure 2. The same program read for results. Left: evidence produced by funded investigators against a comparable unfunded group. Right: outcomes reported by accredited providers, by Moore level, across a year of funded activities. Illustrative example built on synthetic data; no client data is shown.
These questions work for one reason: the programs, the expert profiles and the engagement history are on the same system, and the AI reads across all of them under the same permission rules that govern who sees what in the program itself. A capability bolted onto a grants system alone can’t answer most of them, because most of the data it needs isn’t there.
Where the reviewer still sits
None of this removes a person from the decision. The AI does not approve a grant, set a fair market value figure or clear a conflict. It produces the analysis and the record behind it, names the sources it drew on, and a reviewer signs off. When something in the record can’t be verified, a fair market value figure, an investigator credential, a prior payment, it should say so and leave the gap visible. We have published an example of ours doing exactly that [3], and I would ask any vendor for the same before believing a demo.
The compliance floor, and why it is the floor
Grants systems generally cover compliance, and for good reason. The obligations are real.
The rules behind that floor are the federal Anti-Kickback Statute and the Office of Inspector General’s compliance guidance for manufacturers [4][6], the Sunshine Act and its Open Payments reporting [7], the PhRMA Code [8], the ACCME Standards for Integrity and Independence [9] and, in Europe, the EFPIA Code [10]. When a company funds an investigator-initiated study, the FDA rules for sponsors and investigators at 21 C.F.R. Part 312 apply as well [11].
Grants systems generally handle request submission, routing, committee review, contracting and payment tracking. That is the floor. What separates a program that can defend itself at audit from one that can’t is the quality of the record behind each decision: who reviewed it, on what basis, against what fair market value standard, with what conflict check, and what the program produced as a result. And what separates a program that runs as an administrative function from one that runs as part of the company’s medical and market development strategy is the ability to ask questions across its own history. The floor doesn’t give you that.
Eight questions to put to any grants or investigator study vendor
These are the questions I would want answered in writing before signing up, and they are the ones we expect to be asked ourselves.
Can your system answer a question that draws on the grants record, the investigator’s profile and the company’s engagement history in a single session, or do I have to export and reconcile?
How does the AI inherit the permission model that separates medical from commercial activity? Can a commercial user, or a commercial-facing agent, see anything about a pending request?
When the AI produces a recommendation on a grant or a study, what in the record shows a reviewer that it was AI-produced, which sources it drew on, and what the reviewer changed?
What does the system do when a fair market value figure, an investigator credential or a prior payment can’t be verified from the record? Show me a published example of it declining to answer.
How many grants and investigator study programs have you administered end to end, from concept through outcomes reporting, over how many years?
Can my administrators change forms, routing rules, reviewer pools and thresholds without a vendor release or a paid project? What happens to my configuration and history at each release?
Can the system show what funded work produced afterward: publications, trials and congress activity for funded investigators against a comparable unfunded group, and provider-reported outcomes by Moore level aggregated across a grants portfolio?
Who owns the program record at the end of the term, in what format does it leave, and how long is it retained after termination?
Who wrote this, and why
I lead operations and client solutions at SteepRock, which means the teams that implement our systems, support our clients day to day, and sit with them while they put the work to use. I joined SteepRock in 2004, and the 2008 investigator-initiated research deployment for a top-ten pharmaceutical company described below was one of my early engagements. I have worked on grants and investigator-initiated study programs continuously since. The questions in this article are the ones I hear from many program managers and compliance officers we work with.
SteepRock has administered these programs continuously since it put a dedicated investigator-initiated research system, with a fully integrated backend database, into production for a top-ten pharmaceutical company in 2008. Those programs run today through EGS and ISTS on a single-tenant, backward-compatible platform that has carried client configurations forward across every release. Since 2025 the finished reporting these programs need has been produced by SteepRock Embedded Intelligence and included in the license, with no charge by the document or by the question.
References
SteepRock, Inc., What the Price of AI Work in Pharma Cannot Tell You Before You Buy It, September 2026. Companion article on results as a service and the pricing of AI-produced work in life sciences.
SteepRock, Inc., client deliverables on file: quarter-to-date grants executive report (June 2026) and request cycle time analysis (August 2026), produced by SteepRock Embedded Intelligence from the client’s portal data. Client name withheld.
SteepRock, Inc., When the Number Is Wrong, the AI Should Say So, September 2026. Case study with the client’s anonymized prompts and cited references. https://www.steeprockinc.com/when-the-number-is-wrong-the-ai-should-say-so
U.S. Department of Health and Human Services, Office of Inspector General, Compliance Program Guidance for Pharmaceutical Manufacturers, 68 Fed. Reg. 23731, May 5, 2003.
U.S. Department of Health and Human Services, Office of Inspector General, Special Fraud Alert: Speaker Programs, November 16, 2020. https://oig.hhs.gov/fraud/docs/alertsandbulletins/2020/SpecialFraudAlertSpeakerPrograms.pdf
U.S. Department of Health and Human Services, Office of Inspector General, General Compliance Program Guidance, November 6, 2023. https://oig.hhs.gov/documents/compliance-guidance/1135/HHS-OIG-GCPG-2023.pdf
Physician Payments Sunshine Act, section 6002 of the Patient Protection and Affordable Care Act, implemented at 42 C.F.R. Part 403, Subpart I.
Pharmaceutical Research and Manufacturers of America, Code on Interactions with Health Care Professionals, revised effective January 1, 2022. https://phrma.org/codes-and-guidelines/code-on-interactions-with-health-care-professionals
Accreditation Council for Continuing Medical Education, Standards for Integrity and Independence in Accredited Continuing Education, adopted December 2020. https://www.accme.org/accreditation-rules/standards-for-integrity-independence-accredited-ce
European Federation of Pharmaceutical Industries and Associations, EFPIA Code of Practice, Final Consolidated Version 2026 (adopted by the EFPIA Board on 22 March 2019 and ratified by the General Assembly on 27 June 2019; consolidated version updated 4 March 2026), Articles 12, 13, 15, 16, 18 and 23. https://www.efpia.eu/media/uzqpperi/efpia-code-of-practice-2026.pdf
U.S. Food and Drug Administration, 21 C.F.R. Part 312: definition of sponsor-investigator at § 312.3 and responsibilities of sponsors and investigators at Subpart D.
References
SteepRock, Inc., What the Price of AI Work in Pharma Cannot Tell You Before You Buy It, September 2026. Companion article on results as a service and the pricing of AI-produced work in life sciences.
SteepRock, Inc., client deliverables on file: quarter-to-date grants executive report (June 2026) and request cycle time analysis (August 2026), produced by SteepRock Embedded Intelligence from the client’s portal data. Client name withheld.
SteepRock, Inc., When the Number Is Wrong, the AI Should Say So, September 2026. Case study with the client’s anonymized prompts and cited references. https://www.steeprockinc.com/when-the-number-is-wrong-the-ai-should-say-so
U.S. Department of Health and Human Services, Office of Inspector General, Compliance Program Guidance for Pharmaceutical Manufacturers, 68 Fed. Reg. 23731, May 5, 2003.
U.S. Department of Health and Human Services, Office of Inspector General, Special Fraud Alert: Speaker Programs, November 16, 2020. https://oig.hhs.gov/fraud/docs/alertsandbulletins/2020/SpecialFraudAlertSpeakerPrograms.pdf
U.S. Department of Health and Human Services, Office of Inspector General, General Compliance Program Guidance, November 6, 2023. https://oig.hhs.gov/documents/compliance-guidance/1135/HHS-OIG-GCPG-2023.pdf
Physician Payments Sunshine Act, section 6002 of the Patient Protection and Affordable Care Act, implemented at 42 C.F.R. Part 403, Subpart I.
Pharmaceutical Research and Manufacturers of America, Code on Interactions with Health Care Professionals, revised effective January 1, 2022. https://phrma.org/codes-and-guidelines/code-on-interactions-with-health-care-professionals
Accreditation Council for Continuing Medical Education, Standards for Integrity and Independence in Accredited Continuing Education, adopted December 2020. https://www.accme.org/accreditation-rules/standards-for-integrity-independence-accredited-ce
European Federation of Pharmaceutical Industries and Associations, EFPIA Code of Practice, Final Consolidated Version 2026 (adopted by the EFPIA Board on 22 March 2019 and ratified by the General Assembly on 27 June 2019; consolidated version updated 4 March 2026), Articles 12, 13, 15, 16, 18 and 23. https://www.efpia.eu/media/uzqpperi/efpia-code-of-practice-2026.pdf
U.S. Food and Drug Administration, 21 C.F.R. Part 312: definition of sponsor-investigator at § 312.3 and responsibilities of sponsors and investigators at Subpart D.
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For more than 20 years, SteepRock has served as a recognized thought leader and best in class strategic partner across the pharmaceutical, biotech, medical device, animal health, and nutrition industry segments. Your success is our success. We deliver technology, information and analytics to help support the most critical business decisions shaping the healthcare landscape and support the entirety of your business with AI making you and your team more efficient and responsive.
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SteepRock helps medical affairs and commercial teams at pharma, biotech, and medical device companies identify, profile, and engage the KOLs, DOLs, HCPs, healthcare organizations, and payers that matter to their products. Since 2001. 400+ clients.
Copyright © 2026 SteepRock Inc. SteepRock is a registered trademark of SteepRock, Inc. All rights reserved.
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Want to speak with us directly?
Enter your phone number and we will give you a call
We can help you achieve your goals
For more than 20 years, SteepRock has served as a recognized thought leader and best in class strategic partner across the pharmaceutical, biotech, medical device, animal health, and nutrition industry segments. Your success is our success. We deliver technology, information and analytics to help support the most critical business decisions shaping the healthcare landscape and support the entirety of your business with AI making you and your team more efficient and responsive.
Products
Resources
Articles
SteepRock helps medical affairs and commercial teams at pharma, biotech, and medical device companies identify, profile, and engage the KOLs, DOLs, HCPs, healthcare organizations, and payers that matter to their products. Since 2001. 400+ clients.
Copyright © 2026 SteepRock Inc. SteepRock is a registered trademark of SteepRock, Inc. All rights reserved.
Phone
Want to speak with us directly?
Enter your phone number and we will give you a call
We can help you achieve your goals
For more than 20 years, SteepRock has served as a recognized thought leader and best in class strategic partner across the pharmaceutical, biotech, medical device, animal health, and nutrition industry segments. Your success is our success. We deliver technology, information and analytics to help support the most critical business decisions shaping the healthcare landscape and support the entirety of your business with AI making you and your team more efficient and responsive.
Products
Resources
Articles
SteepRock helps medical affairs and commercial teams at pharma, biotech, and medical device companies identify, profile, and engage the KOLs, DOLs, HCPs, healthcare organizations, and payers that matter to their products. Since 2001. 400+ clients.
Copyright © 2026 SteepRock Inc. SteepRock is a registered trademark of SteepRock, Inc. All rights reserved.