Evidence needs are prioritized within departments.
Clinical endpoints, payer questions, safety concerns, regulatory commitments, medical insights, patient outcomes, and launch needs are planned separately.
Evidence Generation Planning
Turn lifecycle evidence needs into one governed execution plan.
StromaOS connects strategic evidence questions, clinical studies, RWE, HEOR, safety, regulatory, market access, medical affairs, dependencies, priorities, budgets, decisions, and outcomes in one governed evidence generation plan.
Connected cross-functional evidence needsGoverned priorities and dependenciesVisible gaps, budgets, and timingTraceable evidence decisions
The evidence planning problem
Every function has an evidence plan. The company rarely has one.
Clinical, regulatory, safety, HEOR, access, medical affairs, and commercial teams generate evidence for different decisions, audiences, markets, and timelines. Without a shared plan, studies overlap, gaps persist, dependencies surface late, and the same evidence is funded repeatedly.
Teams commission similar studies for different stakeholders.
Overlapping RWE, burden, treatment-pattern, utility, subgroup, and outcomes work is difficult to identify before budgets are committed.
Studies are approved without explicit connection to the decision they must change.
The intended use, stakeholder, claim, timing, minimum evidence threshold, alternative path, and consequence of delay are often unclear.
Automation can rank ideas without owning strategic trade-offs.
AI can identify gaps, compare options, and simulate scenarios, but cannot independently allocate budget, cancel a study, accept evidence risk, or change portfolio priorities.
Cross-cutting capabilities
One governed portfolio of evidence questions, activities, decisions, and outcomes.
Evidence Generation Planning activates across multiple StromaOS modules to coordinate evidence strategy, execution, reuse, and lifecycle learning.
Strategic question registry
Capture the decision, stakeholder, population, claim, market, timing, uncertainty, current evidence, threshold, and consequence of inaction.
- Decision-bound evidence questions
- Stakeholder and market context
- Evidence sufficiency thresholds
- Gap and urgency classification
Existing evidence and activity map
Connect planned, active, completed, paused, and proposed studies, analyses, models, registries, publications, and data assets.
- Cross-functional activity inventory
- Overlap and duplication detection
- Dependency and reuse mapping
- Coverage by claim and decision
Evidence option and design planning
Compare trials, RWE, analyses, HEOR models, translational work, surveys, literature synthesis, and mixed-method approaches.
- Design and data-source options
- Feasibility and time-to-evidence
- Bias, quality, and acceptance risk
- Primary and fallback pathways
Evidence portfolio optimization
Prioritize work using decision impact, strategic relevance, urgency, feasibility, cost, timing, dependencies, reuse, and risk.
- Transparent scoring criteria
- Scenario and constraint modeling
- Budget and capacity allocation
- Trade-off and opportunity-cost review
Plan-to-activity governance
Link every approved evidence priority to a protocol, analysis, model, owner, budget, milestone, output, review, and intended use.
- Owner and milestone control
- Cross-functional dependency tracking
- Risk and issue escalation
- Decision and output readiness
Evidence use and outcome tracking
Measure whether the evidence changed a regulatory, clinical, safety, payer, medical, or portfolio decision and whether further work is needed.
- Evidence-to-decision linkage
- Claim and stakeholder use
- Outcome and impact review
- Gap closure and plan adaptation
Governed workflow
Move from evidence need to approved portfolio action in a controlled sequence.
Every step retains the decision question, evidence state, option, assumptions, reviewer, authority, budget, owner, output, and outcome.
STEP 01
Frame the decision need
Clinical, regulatory, safety, payer, medical, patient, scientific, commercial, or portfolio decision.
STEP 02
Assess existing evidence
Available data, studies, analyses, models, gaps, quality, applicability, uncertainty, and stakeholder acceptance.
STEP 03
Design evidence options
Study type, data source, population, comparator, outcomes, method, timing, cost, risks, and alternatives.
STEP 04
Prioritize the portfolio
Decision impact, urgency, feasibility, dependencies, reuse, capacity, budget, opportunity cost, and scenario.
STEP 05
Approve and execute
Funding, owner, milestones, quality gates, reviews, outputs, escalation, and accountable human authority.
STEP 06
Measure and adapt
Evidence use, decision impact, claim support, stakeholder response, residual gap, lessons, and next action.
Evidence portfolio readiness
An evidence activity should remain connected to the decision, stakeholder, budget, and lifecycle use that justify it.
StromaOS treats evidence questions, studies, analyses, models, outputs, claims, commitments, and decisions as connected governed objects.
Portfolio review becomes faster because overlap, gaps, dependencies, priorities, risks, ownership, and expected decision value are visible in one place.
Model an evidence portfolioGovernance inside the layer
AI can optimize evidence options without inheriting portfolio, budget, or scientific authority.
StromaOS separates question framing, evidence assessment, option generation, prioritization, recommendation, funding, study approval, execution, interpretation, and lifecycle use.
Explore the Governance Spine01
Decision-bound evidence governance
Every proposed activity must identify the decision, stakeholder, timing, threshold, evidence gap, expected use, and consequence of not acting.
02
Option and assumption transparency
Study design, source, population, endpoints, methods, cost, timeline, feasibility, bias, acceptance risk, and alternatives remain explicit.
03
Portfolio and budget control
Prioritization criteria, funding ranges, capacity limits, dependencies, opportunity costs, trade-offs, and decision rights are governed before execution.
04
Human investment authority
AI may identify gaps, compare options, and simulate scenarios. Qualified scientific, clinical, regulatory, safety, access, medical, finance, and portfolio leaders retain approval authority.
05
Evidence Data Trace
Questions, sources, assumptions, options, scores, versions, reviews, approvals, funding, studies, outputs, claims, decisions, and outcomes remain reconstructable.
Method routing
Use the right method for each evidence planning task.
Evidence Generation Planning routes work through deterministic analytics, version-controlled statistics, machine learning, local scientific models, governed hosted models, human review, or expert adjudication.
TIER 01Analytical
Inventory, coverage, dependencies, timelines, budgets, rules, scoring, status, and deterministic portfolio calculations.
TIER 02Statistical
Power, precision, uncertainty, expected information, evidence weighting, forecasting, and version-controlled analytical workflows.
TIER 03Machine Learning
Gap classification, similarity, duplication detection, impact prediction, prioritization, and model evaluation.
TIER 04Local Scientific AI
Private local models for question synthesis, option development, planning support, and internal portfolio knowledge.
TIER 05Hosted AI
Approved external models invoked with controlled data, purpose, logging, cost, and output handling.
TIER 06Human
Scientific, clinical, safety, regulatory, HEOR, access, medical, finance, portfolio, and governance review and authorization.
TIER 07Panel of Experts
Structured adjudication for disputed priorities, uncertain evidence value, or high-consequence portfolio investment decisions.
Governed agent execution
Agents operate as a controlled evidence planning office.
Each agent receives a defined role, evidence scope, permitted tools, intelligence tiers, quality requirements, escalation conditions, and authority ceiling.
Evidence portfolio coordinator
Frames the decision need, coordinates cross-functional evidence inputs, tracks options and dependencies, reconciles priorities, and prepares the governed investment package.
- Decision and question framing
- Cross-functional evidence coordination
- Portfolio and dependency management
- Investment-package readiness
Evidence design and portfolio specialists
Perform bounded gap, literature, study-option, data-source, feasibility, cost, timeline, overlap, scoring, and scenario tasks using approved methods.
- Evidence-gap analysis
- Study and data-source options
- Portfolio overlap and dependency review
- Scenario and prioritization support
Governance and investment control
Checks question quality, source eligibility, scoring criteria, assumptions, duplication, budget authority, required review, approval state, and traceability.
- Policy enforcement
- Question and option control
- Budget and approval gating
- Evidence Data Trace
Cross-lifecycle outcomes
Evidence investment becomes more strategic because questions, activities, budgets, and decisions stay connected.
The value is not a larger study list. The value is a governed portfolio that directs evidence generation toward the decisions that matter most.
See every major evidence need in one place.
Connect questions, stakeholders, claims, markets, studies, analyses, models, commitments, dependencies, timing, and owners.
Fund evidence based on decision value.
Make impact, urgency, feasibility, cost, timing, risk, reuse, opportunity cost, and authority explicit before approval.
Reuse evidence across functions and markets.
Identify where one study, analysis, model, dataset, or evidence object can serve regulatory, safety, access, and medical needs.
Expand AI without outsourcing portfolio judgment.
Allow more automation inside explicit question, option, assumption, score, budget, review, approval, and evidence-use boundaries.
Start with one asset, indication, or launch where evidence plans are fragmented across functions.
Connect the current studies, analyses, models, commitments, claims, budgets, and decisions. Define the question registry, prioritization model, decision rights, funding gates, and evidence-use record. Then run evidence generation as one governed portfolio.