Top Risk Areas for Internal Audit: Life Sciences

As life sciences organizations approach 2026, they face a high-stakes risk environment shaped by rapid innovation, global regulation, and financial pressures. AI-driven research and development (R&D), connected medical devices, and decentralized clinical trials are introducing new vulnerabilities across operations, product security, and supply chains. Meanwhile, patent expirations and evolving disclosure and pricing rules are transforming the commercial landscape and pushing internal audit to broaden its scope.

Five priority risk areas for internal audit in life sciences companies to focus on in 2026 include:

• Medical device cybersecurity: Networked devices create risks beyond data loss, impacting patient safety and care continuity. Internal audit should address both cybersecurity and supply chain dependencies. 
• AI and data integrity: AI accelerates R&D but raises concerns around bias, governance, and compliance. Internal audit should validate model controls and reliability. 
• Trial integrity and DISE readiness: Decentralized trials require robust data oversight and corrective and preventive action (CAPA) systems. Internal audit must also assess readiness for the Financial Accounting Standards Board’s (FASB’s) disaggregation of income statement expenses (DISE) reporting requirements. 
• Patent cliff and market access: As exclusivity ends, internal audit should evaluate life cycle planning, pricing, and reimbursement strategies.
• Supply chain resilience: Internal audit should review logistics, contract development and manufacturing organization (CDMO) risk, and regulatory compliance across global sourcing and distribution. 

Internal audit’s ability to align innovation, compliance, and financial transparency will be essential in guiding life sciences organizations through this next phase of transformation.

Medical device cybersecurity  

As medical devices become more software-driven and cloud-connected, risks once confined to IT now directly affect patient care. Weak encryption, outdated firmware, or insecure interfaces can enable unauthorized access, data manipulation, or even loss of device control.

Why the risk?

Despite these threats, connected devices bring major benefits, real-time data sharing, faster diagnoses, remote monitoring, and cost savings through predictive maintenance. But these advantages can quickly be lost if internal audit doesn’t keep pace with the evolving threat landscape.

High-value targets

Healthcare providers are prime targets for threat actors such as ransomware groups, nation-states, and data brokers. Beyond financial gain, attackers seek research data, infrastructure disruption, and sensitive patient information, all of which makes connected healthcare systems particularly vulnerable.

Supply chain risk

Many devices rely on third-party components and software. A single weak link, like untested firmware, can compromise multiple systems. Internal audit should assess supplier risk management, ensuring cybersecurity clauses, testing protocols, and patch processes are clearly defined and enforced.

From data loss to patient harm

Cyber incidents involving medical devices pose more than financial or operational risk. They can endanger lives. A compromised device like a ventilator isn’t just a technical issue; it’s a clinical emergency. Internal audit teams must evaluate risk through a patient safety lens, prioritizing controls that protect both care continuity and human health.

Next steps for internal auditors

• Device security controls: Evaluate effectiveness of controls protecting patient safety, data confidentiality, and system availability. 
• Clinical cyber risk: Assess potential impacts of cyber incidents on device operability and care continuity.
• Third-party device risk: Review supplier security, including contract terms for testing, disclosure, and patching.
• Regulatory compliance: Verify alignment with the Food and Drug Administration (FDA), the European Union’s (EU’s) medical device regulation and in vitro diagnostic regulation, and National Institute of Standards and Technology cybersecurity standards.
• Incident response: Test readiness to detect, contain, and recover from device-related cyber events. 
• Life cycle management: Confirm secure practices from design to decommissioning for connected medical devices.

AI and data integrity

AI is transforming life sciences and driving faster discovery, streamlined trials, and precision diagnostics. But with rapid adoption comes significant ethical, regulatory, and technical risks. For internal audit, 2026 presents a critical opportunity to strengthen AI governance, data integrity, and model oversight.

AI governance

AI use across R&D, clinical, and commercial functions raises issues around bias, transparency, and accountability, especially when relying on third-party tools. Weak governance can lead to ethical lapses and compliance failures. Internal audit should evaluate whether frameworks define risk ownership, regulate the model life cycle, and align with standards like the EU AI Act and FDA guidance. Accountability and validation checkpoints are essential for responsible AI use.

Data integrity in clinical trials

AI tools now support decentralized trials, managing recruitment, data capture, and monitoring, which increases risks to data quality, traceability, and privacy.

Internal audit should verify compliance with good clinical practice (GCP) guidelines, EU’s General Data Protection Regulation (GDPR), and the Health Insurance Portability and Accountability Act, confirm reliable audit trails, and assess explainability of AI decisions to support regulatory and scientific credibility.

AI in discovery and diagnostics

AI improves R&D speed and diagnostic accuracy, but it also heightens risks around data bias, reproducibility, and validation. Internal audit teams should confirm that models are tested for bias, thoroughly documented, and continually monitored to maintain accuracy and interpretability.

Next steps for internal auditors

• AI governance: Assess oversight, policy frameworks, and risk ownership alignment with enterprise risk management (ERM) and regulatory standards.
• Regulatory readiness: Evaluate compliance with the EU AI Act, FDA guidance, and other evolving global AI regulations.
• Clinical trial data integrity: Test controls for traceability, explainability, and integrity in AI-enabled trials. 
• Model validation: Verify life cycle processes for bias testing, accuracy checks, and documentation.
• Third-party AI tools: Review validation and oversight of external AI used in R&D, clinical, and diagnostic settings.
• AI ethics: Assess integration of fairness, transparency, and responsible use principles in AI applications. 
• AI cybersecurity: Evaluate access controls and protection of training data and model repositories from tampering.

Trial integrity and DISE readiness

Clinical trials are foundational to life sciences innovation and reputation. They shape regulatory approvals, investor confidence, and public trust. As trials grow more global, decentralized, and digital, maintaining data integrity and operational control becomes increasingly complex, and essential.

The convergence of advanced technologies, outsourced models, and evolving regulatory expectations is reshaping the clinical landscape. These shifts have created new opportunities for innovation as well as new vulnerabilities, particularly regarding oversight, quality management, and information reliability. Internal audit should focus on the following key areas:

CAPA effectiveness

CAPA systems are central to clinical compliance. Regulators expect root cause analysis and effective, lasting solutions. Weak CAPA practices can lead to repeated violations and threaten trial integrity. With increasing reliance on third parties, complex treatments, and AI, internal audit should assess whether CAPA systems are evolving to meet these demands and maintain regulatory readiness.

Data integrity and governance

Most clinical data now flows through digital platforms. Compliance with GCP and good practice (GxP) guidelines requires accuracy, traceability, and secure retention. Internal audit should evaluate system validation, governance, and whether controls ensure data reliability, including for downstream uses like financial reporting.

DISE readiness

FASB’s 2024 accounting standards update (ASU) on DISE requires public companies to itemize R&D and clinical trial expenses by 2026. Internal audit teams should assess whether accounting systems and processes are ready by focusing on expense classification, finance, R&D integration, and reconciliation testing to support transparent and accurate reporting.

Next steps for internal auditors

• CAPA system audit: Evaluate whether CAPA processes effectively identify root causes, implement fixes, and prevent recurrence. 
• Clinical data integrity: Assess controls ensuring trial data reliability, traceability, and GCP and GxP compliance. 
• Trial operations and spend: Review governance of clinical budgets, forecasting, and regulatory compliance.
• CRO oversight: Test vendor performance, contract adherence, and quality management across third-party contract research organizations (CROs). 
• R&D and finance integration: Confirm that R&D costs are accurately captured and aligned with DISE reporting needs. 
• DISE readiness: Evaluate financial systems, categorization logic, and disclosure controls for ASU 2024-03 compliance. 
• Clinical staffing audit: Assess recruiting, onboarding, and retention strategies for compliance-critical clinical roles. 

Patent cliff and market access

The upcoming patent cliff and increasing pricing and market-access pressures pose significant financial and strategic risks for life sciences companies. As top-selling drugs lose exclusivity, revenue declines from generic and biosimilar competition are expected. At the same time, governments and payers are tightening cost controls, implementing price negotiations, and enforcing stricter reimbursement rules.

This convergence threatens profitability and the ability to fund future innovation. Declining pricing power and delayed reimbursement reduce cash flow, which limits R&D investment and slows therapy launches. Internal audit should assess whether the organization has built resilience into forecasting, portfolio governance, and pricing strategies.

R&D pipeline and life cycle management 

With many major patents expiring by 2030, companies must strategically manage product life cycles to sustain value through reformulations, new indications, or combination therapies. R&D governance can help ensure that resources target high-impact, compliant projects aligned with long-term goals.

Internal audit focus areas include:

• Effectiveness of R&D portfolio governance 
• Transparency in investment decisions 
• Controls for life cycle changes and data integrity post-approval 

Evaluating how innovation is governed helps manage risk during the patent cliff period.

Pricing and reimbursement 

Pricing uncertainty is intensifying as cost pressures and shifting health technology assessments (HTAs) demand more evidence of value. Post-exclusivity generics lower prices, and payers might restrict access or renegotiate reimbursement.

Internal audit should assess:

• Controls for pricing, contracts, and rebate management 
• Scenario planning for patent expiry 
• Governance over market access and payer engagement 

By strengthening oversight in these areas, internal audit can support financial stability and strategic adaptability in a tightening market.

Next steps for internal auditors

• ERM integration: Assess how leadership incorporates patent loss, pricing, and reimbursement risks into enterprise risk planning. 
• GTN and rebate controls: Evaluate controls over gross-to-net (GTN) calculations, payer contracts, and rebate accuracy. 
• R&D and life cycle governance: Review how R&D priorities and product life cycle management are structured and funded. 
• Market access and pricing: Test controls supporting pricing strategy, HTA submissions, and reimbursement planning. 
• Pipeline forecasting: Assess models forecasting revenue replacement and innovation sustainability post-patent expiration. 
• Regulatory disclosures: Verify completeness and accuracy of public disclosures on pricing and pipeline risk. 

Supply chain resilience

Global sourcing helps life sciences companies expand access and control costs, but it also introduces significant risk. Disruptions in shipping, evolving trade rules, regulatory expectations, and third-party data access can affect product flow, inventory, and compliance. Internal audit plays a critical role in assessing whether supply chains remain resilient and adaptable.

Logistics and cold chain reliability 

Life sciences companies face growing instability regarding logistics. Shifting routes, limited air freight, and delays can spoil temperature-sensitive products. Just-in-time models now magnify disruption impacts, and even intact deliveries complicate planning when timing is unpredictable.

Track-and-trace systems add value only if data is complete and promptly reviewed. Gaps in temperature records or delayed responses can trigger compliance issues. Internal audit should treat logistics as a cross-functional system that evaluates alternate routes, deviation response, and evidence of real-time control.

Supplier and CDMO risk 

Outsourcing accelerates delivery, but it also concentrates risk. Dependence on a few suppliers for application programming interfaces, packaging, or testing means a single disruption can cascade. Tech transfers and site qualifications take time that regulators and patient needs might not allow.

Internal audit should verify dependency maps, backup plans, and enforceable contracts. Effective oversight includes on-site presence, enhanced sampling, and third-party validation of remediation.

Traceability and cyber resilience 

Various regulations, such as the Drug Supply Chain Security Act (DSCSA), EU critical medicines guidance, and the EU Network and Information Systems 2 Directive, require tighter traceability and cyber defenses. Serialization gaps, slow verifications, or vulnerable shared systems can block shipments.

Internal audit should assess the organization’s ability to trace products, manage partner access, and contain cyber events. Tabletop simulations, clear escalation roles, and strong data quality routines are key indicators of readiness.

Trade and forced-labor compliance 

Rapid changes in tariffs, customs, and labor laws can lead to shipment detentions, penalties, or reputational harm. Risks often stem from sub-tier suppliers with poor traceability.

Internal audit should confirm compliance is routine, not annual. enterprise resource planning systems, not spreadsheets, should house origin data. Routine screening, audit rights, and alternative sourcing strengthen resilience.

IP and commercial pressures 

Supply chain decisions now reflect intellectual property (IP) and pricing risk as much as production capacity. AI-based research must meet patent requirements, while data restrictions in countries like China limit collaboration. Pricing reforms, such as U.S. Medicare Part D and the UK’s Voluntary Scheme for Branded Medicines Pricing, Access and Growth, affect demand and revenue.

Internal audit should verify that data is secured, AI contributions are documented, and supply planning adjusts to market shifts through formal governance, not informal fixes. Alignment among IP, pricing, and operations helps preserve product flow and enterprise value.

Next steps for internal auditors

• Logistics and cold chain resilience: Assess controls for temperature-sensitive and single-source products, including alternate routes and deviation handling. 
• Supplier and CDMO risk: Map critical supplier dependencies, verify contingency plans, and review audit coverage and frequency. 
• Traceability and cybersecurity: Validate DSCSA compliance, serialization accuracy, and the ability to contain cyber events across the supply chain.
• Trade and labor compliance: Confirm adherence to the Uyghur Forced Labor Prevention Act and customs rules through supplier screening, traceability, and documentation. 
• IP and data security: Evaluate access controls, IP ownership documentation, and data-sharing protections across R&D and manufacturing. 
• Commercial alignment: Review how pricing, access, and regulatory changes are reflected in supply planning and inventory management. 
• Supplier quality and CGMP: Test oversight of manufacturing partners for compliance with current good manufacturing practices (CGMP) and data integrity standards. 
• Crisis and continuity readiness: Assess readiness for disruptions through crisis simulations, escalation protocols, and recovery plans. 

Looking ahead

As life sciences organizations enter 2026, internal audit must balance innovation with control so that rapid technological and regulatory change does not outpace governance. From AI-enabled R&D to connected medical devices and decentralized trials, each advancement introduces new risks that demand vigilant oversight and coordination across compliance, IT, and operational functions.

To stay ahead, internal audit must adopt a forward-looking, data-driven approach that emphasizes agility, transparency, and cross-functional collaboration. By focusing on cybersecurity, data integrity, financial reporting readiness, market sustainability, and supply chain resilience, internal auditors can strengthen enterprise resilience, protect patient safety, and reinforce stakeholder confidence in a rapidly evolving global health landscape.