Why Mid-Cap Biotech Governance Is Different

The data governance literature is dominated by two archetypes: the large pharma enterprise with a Chief Data Officer, a Data Management Office, and a dozen domain councils; and the early-stage startup where governance means whoever runs the analytics stack also owns the definitions. Neither template survives contact with a mid-cap biotech.

At 200 to 2,000 employees, a biotech typically has a commercial product or a late-stage clinical program, real regulatory exposure, a growing IT and analytics function, and a leadership team that has not yet added a CDO. Data ownership is distributed across Quality, Clinical Operations, Manufacturing, Commercial, Medical Affairs, and IT, none of whom think of themselves primarily as data owners. When cross-functional data questions arise, and they arise constantly, the default answer is that they get resolved by whoever has the loudest voice in the room, which is usually the function under the most pressure that quarter.

The DAMA-DMBOK framework, the most widely referenced data management body of knowledge, describes a governance structure with a Data Management Office, a Data Council, and domain-level data leadership.1 The framework is sound, but the personnel implications are heavy. Attempting to instantiate all three tiers at a mid-cap biotech typically produces one of two failure modes: either the council becomes a paperwork ceremony because there is not enough staff to feed it real work, or the roles get assigned to people already fully loaded with day jobs, and the governance function starves.

31% of pharma companies have a fully implemented data governance strategy3
35% of Chief Data and Analytics Officers rank governance as the top success factor3
15% customer satisfaction lift from product-and-platform operating models9

The mid-cap answer is a single-tier council with real authority and a deliberately narrow scope, supported by two focused sub-committees and a small operational team. This is not a scaled-down enterprise model. It is a different model, designed around the constraint that governance work has to be shouldered by people who already have functional roles, and the compensating advantage that decision-makers can actually fit in one room.

The mid-cap principle. Do not replicate an enterprise governance chart at a fraction of the personnel. Design for the constraint you actually have, which is a leadership team of roughly ten to fifteen people who will decide most cross-functional questions, whether or not you convene them formally.

Council Composition: Who Sits at the Table

The temptation is to make the council large. Every function wants a seat, and it is politically easier to include someone than to exclude them. Resist. A council of fifteen people rarely makes decisions; it schedules the meeting where the actual decision-makers will meet later.

The composition below aims for eight to eleven voting members, plus rotating attendees for topic-specific input. Every voting member has to bring both organizational authority for their function and enough operational literacy in data topics to make informed calls. If your VP of Commercial cannot tell you within two questions who owns the HCP master file, they are not ready to be a voting member yet, and you need a preparation conversation before the first meeting.

Voting members

  • Chair: typically the most senior data-adjacent executive, often the CIO, CTO, VP of IT, or a Chief Data and Analytics Officer where the role exists. In smaller biotechs, this may be the COO. The Chair has tie-breaking authority and owns the escalation path to the CEO.
  • Chief Data Officer or equivalent: where the role exists, holds the executive sponsor position and owns the Data Management Office function.8 Where it does not, this responsibility rolls into the Chair.
  • Head of Quality: represents GxP data, quality management system data, and audit posture. Non-optional.
  • Head of Regulatory Affairs: represents submission data, health authority interactions, and the interpretation of regulatory guidance on data integrity.
  • Head of Clinical Operations or Clinical Data Management: represents clinical trial data, EDC systems, and vendor data flows.
  • Head of Manufacturing or Technical Operations: represents MES data, batch records, and manufacturing analytics.
  • Head of Commercial or Commercial Operations: represents CRM, HCP and HCO master data, brand analytics, and market access data.
  • Head of Medical Affairs: represents medical information, real-world evidence, and scientific communications data.
  • Head of Human Resources or People: represents workforce data, privacy of employee records, and access provisioning.
  • Chief Information Security Officer or Head of Security: represents access controls, breach response, and third-party risk.
  • General Counsel or Head of Privacy: represents GDPR, HIPAA, contractual constraints, and regulatory reporting obligations.

Non-voting standing attendees

  • Data Governance Lead: the operational owner of the council function. Sets the agenda, tracks decisions, chases actions between meetings. Typically a Director-level role, often reporting to the CIO or CDO.
  • Enterprise Data Architect: brings technical grounding to definition and integration debates.
  • Compliance or Internal Audit representative: observes and flags audit exposure early.

Rotating attendees

For any given agenda, one or two data stewards, system owners, or subject matter experts attend for the specific topics that require their input. This keeps the core group small while pulling in operational depth when it matters. A frequent mistake is to make stewards permanent members, which either bloats the council or leaves stewards feeling like decorative attendees who cannot actually vote.

A note on the missing CDO. Most mid-cap biotechs do not have a Chief Data Officer. This is fine and even correct at your scale; the role in life sciences is still nascent and CDO tenures are often short.8 What is not fine is skipping the accountability the role would carry. If you do not have a CDO, name the Chair as the accountable executive for the data governance function, put it in their objectives, and give them staff support through the Data Governance Lead.

Decision Rights: Decide, Escalate, Delegate

The single most common failure mode of governance councils is unclear decision rights. Members show up to a meeting expecting to advise, discover partway through that they are being asked to decide, and either rubber-stamp something they do not fully understand or delay the decision to another meeting where the same dynamic repeats.

The decision rights framework below is deliberately explicit. The council is not the venue for every data decision; most decisions should be made at the domain or operational level. The council exists to handle the specific classes of decisions that require cross-functional authority or set precedent for future decisions.

What the council decides

Decision Class Example
Enterprise data domain ownership Who owns the master file for HCPs, sites, products, employees, suppliers.
Enterprise data definitions and standards The canonical definition of “active patient,” “adverse event of interest,” “target account.”
Cross-functional data quality thresholds Acceptable completeness and accuracy rates for shared data, and remediation triggers.
Access rules that cross functions Whether Commercial can access Medical Affairs interaction data; whether R&D can access CRM data for KOL identification.
AI and analytics use case vetting Whether a proposed AI use case can proceed, with what data, and under what oversight.
Repurposing regulated data Any use of GxP data for a non-GxP purpose, such as commercial analytics from manufacturing batch records.
Investments over threshold Data platform investments, master data management programs, and vendor selections above a set dollar amount.

What the council escalates

Not everything belongs at the council. Some decisions require executive authority beyond what a governance body can hold. The council escalates to the CEO, Board, or a subset of the executive team when:

  • The decision involves a change to the risk appetite of the company (for example, whether to use patient-identifiable data for a new AI application).
  • The decision involves a strategic commitment beyond the council’s charter (for example, whether to acquire a data provider).
  • The council cannot reach a decision by qualified majority after two attempts.
  • A decision will materially affect a regulatory filing, health authority interaction, or ongoing inspection.

What the council delegates

The council explicitly delegates authority for classes of decisions to domain owners, data stewards, or sub-committees. Delegation is not abdication; delegated decisions are logged and reviewable, and the council can revoke or modify delegated authority.

DELEGATE TO DOMAIN OWNER

Definitions within a single functional domain

Commercial defines its own segmentation logic. Manufacturing defines its own batch nomenclature. As long as it does not cross functions, it does not need the council.

DELEGATE TO STEWARD

Operational data quality decisions

Whether a specific record is a duplicate. How to resolve a specific data quality exception. Stewards act; council receives metrics.

DELEGATE TO REGULATED SUB-COMMITTEE

GxP data integrity decisions

ALCOA+ interpretation, audit trail review frequency, validation status of new GxP systems.2

DELEGATE TO COMMERCIAL SUB-COMMITTEE

Commercial data operations

HCP master reconciliation cadence, CRM data quality remediation, brand analytics platform decisions below the threshold.

Voting rules

Decisions are made by qualified majority: at least two-thirds of voting members present, with a minimum quorum of six voting members. The Chair has a tie-breaking vote. Any voting member may request that a decision be deferred to the next meeting for further preparation; this deferral is allowed once per topic.

The unanimity trap. Do not require unanimous decisions. In a council of nine to eleven people, unanimity is functionally equivalent to giving any one member a veto, which will be used, and the council will stop making decisions on hard topics. Qualified majority with tie-breaking authority is uncomfortable, and that is the point.

Cadence and Standing Agenda

A monthly council cadence is right for a mid-cap biotech. Quarterly is too slow for the volume of decisions that will accrue, especially in the first year. Biweekly is too frequent to be respected as an executive forum and will degrade into a working group. Monthly gives you twelve real decision-making meetings a year, plus quarterly deep-dives.

Meeting rhythm

  • Monthly council meeting: 90 minutes, chaired by the Chair, staffed by the Data Governance Lead. Attendance is a hard commitment; delegates are allowed but must be pre-briefed and have decision authority for their function.
  • Quarterly deep-dive: half-day session focused on one strategic topic (for example, the AI governance framework, or the enterprise data platform roadmap). Broader attendance welcome.
  • Annual charter review: the council reviews its own charter, decision rights, sub-committee structure, and metrics. Changes require qualified majority.
  • Sub-committees: meet on their own cadence (typically monthly for regulated, biweekly to monthly for commercial), and report a summary into the council monthly.

Standing agenda template

Time Item Purpose
0:00 – 0:05 Approval of prior minutes and decisions Ratify the record so decisions are actionable.
0:05 – 0:15 Sub-committee reports Regulated Data Sub-Committee and Commercial Data Sub-Committee each present a one-page summary of decisions taken and issues escalated.
0:15 – 0:25 Data quality and integrity metrics Standing dashboard: cross-functional data quality scores, open remediation items, aging escalations. Reviewed in a governance forum with authority to act, per MHRA and OECD guidance.2
0:25 – 1:00 Decision items Two to four pre-briefed decisions with recommendation. Each item is presented in five minutes with a written pre-read.
1:00 – 1:20 Discussion item One topic requiring alignment but not yet ready for decision (for example, an emerging AI use case, a new regulatory interpretation).
1:20 – 1:30 Actions, escalations, next meeting preview Confirm accountable owners and dates. Preview next month’s decisions so pre-work can start.

Pre-reads are non-negotiable. Every decision item requires a written pre-read of no more than two pages, distributed at least three business days in advance. This is the discipline that makes a 90-minute meeting productive. Councils that discover the decision detail in the meeting itself will make bad decisions and know it.

Sub-Committees: Regulated and Commercial Data

The two-sub-committee structure reflects the fundamental split in mid-cap biotech data: some of it is regulated by GxP requirements and inspected by health authorities, and some of it is not. Trying to govern both under identical rules produces friction. The regulated data process is heavy for a reason, and applying it to commercial data slows commercial operations. Applying commercial-grade governance to regulated data creates audit exposure.

Regulated Data Sub-Committee

Also called the Data Integrity Council in some organizations, this sub-committee handles all data within the GxP scope: clinical, manufacturing, laboratory, pharmacovigilance, and regulatory. Its charter is anchored in the ALCOA+ principles and the MHRA and PIC/S data integrity guidance.26

REGULATED DATA SUB-COMMITTEE

Chair

Head of Quality or Head of Data Integrity where that role exists.

Members

QA lead, Regulatory Affairs lead, Clinical Data Management lead, Manufacturing IT lead, Laboratory Systems lead, Validation lead, CSV lead.

Scope

GxP system validation status, audit trail review procedures, ALCOA+ compliance monitoring, data integrity investigations, computer system validation strategy, health authority inspection findings related to data integrity.

Escalates to Council when

A finding could affect a submission or an active inspection; a decision requires cross-functional access rules; a repurposing request for GxP data is submitted; a policy change would affect Commercial or IT.

Commercial Data Sub-Committee

Handles all data outside the GxP scope: HCP and HCO masters, market access, brand analytics, sales operations, CRM, marketing performance, medical information (where not regulated), and workforce data. The pace is faster, the tolerance for iteration is higher, and the primary constraints are privacy (GDPR, HIPAA, state laws) and contractual restrictions from data providers.7

COMMERCIAL DATA SUB-COMMITTEE

Chair

Head of Commercial Operations or Head of Data and Analytics.

Members

CRM operations lead, master data lead for HCP/HCO, brand analytics lead, market access data lead, medical information lead (non-regulated aspects), Privacy Officer, Sales Operations lead.

Scope

Master data quality remediation, third-party data contracts and use rules, CRM data governance, commercial analytics platform decisions below threshold, privacy compliance for commercial data.

Escalates to Council when

A cross-functional data definition is proposed; a request touches regulated data; a decision involves an investment above threshold; a privacy or contractual issue could affect the company.

SD perspective on the two-track model. The two-sub-committee structure is not about creating a hierarchy where regulated data is important and commercial is not. It is about matching the pace and formality of governance to the nature of the data. Regulated data requires slow, evidenced, validated changes. Commercial data requires responsive, iterative governance that supports business velocity. Trying to govern both with a single set of rules produces the worst of both worlds: commercial operations that feel slowed by unnecessary formality and regulated operations that feel exposed by insufficient rigor.

Interfacing with QMS and Change Control

Every mid-cap biotech has a Quality Management System, and every QMS has a change control process. The data governance council does not replace these; it interfaces with them at defined points. Failing to make these interfaces explicit is where most councils either duplicate existing processes or create audit gaps.

Where QMS ends and governance begins

QMS and change control govern the validated state of GxP-relevant systems and processes. Changes to a GLP laboratory information management system, a GMP manufacturing execution system, or a clinical electronic data capture system flow through documented change control, with impact assessment, testing, and requalification as needed.4

Data governance covers the semantic layer above this. What does a field mean? Who owns the master version of a reference dataset? Is a business definition consistent across systems? Which data can be used for which purpose? These questions are not always answered by change control, and they cross system boundaries in ways change control usually does not.

The four interface points

1

New system implementations

Any new system that will hold shared data, regulated or not, triggers a data governance review before design freeze. The council or relevant sub-committee reviews data model choices, master data alignment, and integration patterns. QMS validation proceeds in parallel; governance approval is a prerequisite for it.

2

Master data changes

Changes to shared master data (adding a data source to the HCP master, changing product hierarchy) go through data governance approval, then flow into change control for affected validated systems if any. The governance approval is the trigger, not the destination.

3

Data integrity investigations

When a data integrity issue surfaces through audit, inspection, or internal monitoring, the CAPA lives in the QMS. The Regulated Data Sub-Committee is a required consultee on the root cause analysis and remediation plan, and provides the governance-side view of whether policy changes or definition changes are also required.

4

AI and analytics use cases

Any AI or analytics use case using GxP data flows through both the AI use case vetting process (governance) and the applicable validation or qualification process (QMS). Governance approves the use of the data; QMS covers system validation. Neither can substitute for the other.

Documenting the interface

The QMS should be updated to reflect these interfaces explicitly. Standard operating procedures for change control and CAPA should list the Data Governance Council or Regulated Data Sub-Committee as a consultee at the relevant steps, with the definition of what triggers the consultation. This is the audit-critical piece: if governance is running in parallel to QMS without documentation, an inspector will see two undocumented processes and ask hard questions.

Do not let the council become an unwritten process. If the council is making decisions that affect validated systems and those decisions are not documented in either the council’s own records or the QMS, you have created an unwritten process that shadows a validated one. This is the fastest way to turn good governance work into an inspection finding.

Escalation Paths and Dispute Resolution

Escalation paths are the part of a charter that gets tested least often but matters most when tested. Councils that have not clearly defined how disagreements are resolved will discover their inadequacy in the meeting where the disagreement actually happens, which is the worst possible time to work out the process.

Three escalation channels

BOTTOM-UP

From stewards and system owners

An issue that a data steward or system owner cannot resolve within their domain escalates to the relevant sub-committee. If the sub-committee cannot resolve it, or if it crosses regulated and commercial boundaries, it escalates to the council.

CROSS-COUNCIL

Between sub-committees and functions

When Regulated and Commercial Sub-Committees disagree, or when a function represented at the council disputes a sub-committee decision, the council resolves. The Chair sets the agenda placement and pre-brief expectations.

TOP-DOWN

From the council to executive leadership

Decisions the council cannot make, or that exceed the council’s authority, escalate to the CEO and where appropriate the Board. The Chair owns this channel and is expected to use it when needed rather than force the council to a false consensus.

REGULATORY

To Quality and Regulatory Affairs

Any data integrity issue with potential impact on submissions, inspections, or health authority interactions has an immediate escalation path to Quality and Regulatory leadership, independent of the normal council cadence. Speed matters.

Documented dispute resolution

A documented dispute resolution process is a hallmark of a functional governance council; it ensures that conflicts over ownership, data access, or quality rules escalate quickly rather than stalling in individual teams.10 The process the council uses should be simple and written:

  1. The disputing parties attempt resolution at the operational level (steward, system owner, or sub-committee chair).
  2. If unresolved within five business days, the issue is placed on the next council agenda as a decision item, with a written statement of the positions from each party.
  3. The council decides by qualified majority. If the council cannot reach a decision after two agenda placements, the Chair escalates to the CEO with a written summary.
  4. All decisions and escalations are logged. The log is reviewed annually for patterns that suggest a charter or delegation change.

Full Charter Template

The template below is written to be adapted rather than copied. Track changes to the language will be visible to the executive team that ratifies it; do not treat the changes as cosmetic. Every deviation from the template represents a specific design choice about how governance will work at your company.

How to use this template. Read it end to end first. Then work through it section by section with the proposed Chair and two or three intended voting members. The goal of the first drafting session is to surface disagreements about scope and authority; the goal of the second is to close them. Ratify at a subsequent executive meeting.

1. Purpose

The Data Governance Council (“Council”) is the enterprise decision-making body for data-related policies, standards, ownership, definitions, quality thresholds, access rules, and cross-functional data disputes at [Company Name]. The Council exists to ensure that data is managed as a strategic asset in support of patient safety, regulatory compliance, scientific integrity, and commercial performance.

2. Authority

The Council operates under the sponsorship of the [Chief Executive Officer / Chief Operating Officer / Executive Committee] and reports summary of decisions and metrics to the [Executive Committee] on a quarterly basis. The Council has authority to:

  • Ratify enterprise data policies, standards, and definitions.
  • Assign and reassign data domain ownership.
  • Set data quality thresholds and mandate remediation.
  • Approve or deny cross-functional data access requests.
  • Approve or deny AI and advanced analytics use cases involving shared or regulated data.
  • Approve or deny repurposing of GxP data for non-GxP purposes.
  • Delegate authority to sub-committees, domain owners, and data stewards, and revoke such delegation.

The Council does not have authority over:

  • Health authority submissions or interactions (Regulatory Affairs).
  • The validated state of GxP systems (Quality and change control).
  • Personnel or organizational structure (HR and Executive Committee).
  • Legal or contractual determinations (General Counsel).

3. Membership

Voting members are named by title and role in Appendix A. Members are expected to attend in person or via video. Delegates are permitted with the following conditions: they must have decision authority for their function on the agenda items, they must be pre-briefed, and their attendance counts toward quorum. More than two consecutive absences by a voting member without a qualified delegate is grounds for review by the Chair.

4. Chair and officers

The Chair is appointed by the [CEO / Executive Committee] for a two-year term, renewable. The Chair sets the agenda, chairs meetings, holds the tie-breaking vote, and owns the escalation path to executive leadership. The Data Governance Lead is a full-time or dedicated role in [IT / Data Office] responsible for the operational running of the Council, including agenda preparation, minute-taking, decision logging, and inter-meeting follow-up.

5. Cadence

  • Monthly Council meetings, 90 minutes.
  • Quarterly deep-dive sessions, half-day.
  • Annual charter review.
  • Ad-hoc meetings called by the Chair for time-critical decisions.

6. Quorum and voting

Quorum is six voting members. Decisions require a qualified majority of two-thirds of voting members present. The Chair holds a tie-breaking vote. Any voting member may request one deferral per topic; further deferral requires Chair approval.

7. Decision rights framework

The Council decides the classes of decisions listed in Appendix B (“Council Decides”). The Council escalates decisions listed in Appendix B (“Council Escalates”) to the [CEO / Executive Committee]. The Council delegates the classes of decisions listed in Appendix B (“Council Delegates”) to domain owners, sub-committees, and data stewards. The delegation matrix is reviewed annually.

8. Sub-committees

The Council establishes and oversees:

  • Regulated Data Sub-Committee, chaired by [Head of Quality], scope covering GxP data across clinical, manufacturing, laboratory, pharmacovigilance, and regulatory domains.
  • Commercial Data Sub-Committee, chaired by [Head of Commercial Operations], scope covering non-GxP data across commercial, medical affairs, market access, and workforce domains.

Sub-committee charters are appendices to this Charter and are ratified by the Council.

9. Interface with QMS and change control

The Council’s decisions on data policy, definitions, and ownership are documented and referenced in the QMS. Standard operating procedures for change control and CAPA are updated to list the Council or the Regulated Data Sub-Committee as required consultees at the process steps identified in Appendix C. The Council’s decisions on GxP-relevant matters are input to change control, not a substitute for it.

10. Escalation and dispute resolution

Disputes over ownership, definitions, access, or quality rules follow the escalation process defined in Appendix D. Regulatory or data integrity issues with potential submission or inspection impact use the expedited path defined in Appendix D and are notified to Quality and Regulatory Affairs leadership within one business day of identification.

11. Metrics and reporting

The Council monitors and reports on data governance metrics as defined in Appendix E. Standing metrics include: data quality scores by domain, count and aging of open remediation items, count and resolution time of escalated disputes, count of AI use cases reviewed and disposition, and inspection findings related to data.

12. Charter review

This Charter is reviewed annually by the Council. Amendments require a qualified majority vote of the Council and ratification by the [CEO / Executive Committee].

Appendices

  • Appendix A: Voting members by title, with named delegates.
  • Appendix B: Decision rights matrix (Decides / Escalates / Delegates).
  • Appendix C: QMS interface points and referenced SOPs.
  • Appendix D: Escalation and dispute resolution process.
  • Appendix E: Metrics and reporting cadence.
  • Appendix F: Regulated Data Sub-Committee charter.
  • Appendix G: Commercial Data Sub-Committee charter.

Ready-to-adapt template. The template above is deliberately lean. It fits comfortably in a five-page Word document. If your first draft runs to twenty pages, you are describing operations, not chartering the Council. Move the operational content into standard operating procedures or the appendices, and keep the charter focused on authority, membership, decision rights, and interfaces.

The First Ninety Days

A governance council is easier to charter than to make operational. The first ninety days matter disproportionately because they establish whether the council is a real decision-making body or an executive standing meeting people learn to defer.

1

Weeks 1–2: Ratify and staff

Executive team ratifies the charter. Chair is confirmed. Data Governance Lead is named or hired. Voting members are individually briefed and confirm attendance commitment. Sub-committee chairs are named.

2

Weeks 3–4: Inventory the backlog

Data Governance Lead conducts a rapid inventory of open cross-functional data questions, unresolved ownership debates, and pending analytics or AI use cases. This becomes the first three meetings’ worth of agenda material.

3

Weeks 5–6: First council meeting

Focused agenda: ratify sub-committee charters, approve the delegation matrix, and take one or two low-controversy decisions to establish the pattern (pre-read, presentation, discussion, decision, log). Do not overload the first meeting.

4

Weeks 7–8: Sub-committees convene

Regulated and Commercial Sub-Committees hold their first meetings. Chairs establish their own decision logs and reporting formats to the Council.

5

Weeks 9–10: QMS interface documentation

Quality function updates change control and CAPA SOPs to reference the Council and Regulated Data Sub-Committee at the defined interface points. Council reviews and approves.

6

Weeks 11–12: First quarterly deep-dive

Half-day session on the most consequential topic in the backlog: often the AI use case governance framework, or enterprise master data ownership. The output should be a decision or a clearly bounded workstream, not a discussion recap.

Signals of a healthy council at ninety days

  • The decision log has at least eight ratified decisions.
  • No agenda item has been deferred more than twice.
  • Voting member attendance is above 85 percent.
  • Sub-committees are producing summary reports without prompting.
  • At least one dispute has been resolved through the formal process and logged.
  • Quality has integrated the Council into change control SOPs.

Signals of a struggling council at ninety days

  • Meetings are half-full; delegates outnumber principals.
  • The decision log has fewer than three decisions; most items are “discussion continued.”
  • Sub-committee reports are absent or perfunctory.
  • Cross-functional decisions are still being made in parallel forums.
  • The Chair is asking for consensus rather than putting motions to a vote.

The struggling-council signals are not usually fixed by patience. They indicate a design problem: the wrong Chair, the wrong scope, or a decision rights framework that has not actually shifted authority. Diagnose early and adjust the charter through the formal amendment process rather than letting the pattern set.

Conclusion

A data governance council at a mid-cap biotech is not a scaled-down version of enterprise governance. It is a purpose-built structure for a specific organizational scale: one where cross-functional data decisions are frequent enough to need a forum, where the leadership team is small enough to fit in that forum, and where personnel budget cannot support the multi-tier governance operating models designed for large pharma. The council succeeds when it is chartered with clear authority, staffed by voting members who can actually decide, structured around a decision rights framework that keeps the right questions at the right level, and interfaced explicitly with the QMS and change control processes that already govern the company’s regulated state.

Sakara Digital works with pharma and biotech organizations designing and standing up data governance councils, sub-committee structures, and the interface points into their existing quality systems. If you are chartering a council for the first time, revisiting one that has stopped making decisions, or trying to figure out how AI governance fits into the structure you already have, we are happy to have that conversation.