Risk Quantification Engine for Clinical Submission Readiness

Quantifies submission risk using a Failure Modes and Effects Analysis (FMEA)-inspired framework (probability, impact, detectability). Builds risk registers from evidence, computes Risk Priority Numbers (RPN), classifies risk levels, and emits standardized R4SUB (R for Regulatory Submission) evidence table rows via 'r4subcore'. Supports risk mitigation tracking and trend analysis across submission milestones.

r4subrisk

r4subrisk is the risk quantification engine in the R4SUB ecosystem.

It uses an FMEA-inspired framework (Probability x Impact x Detectability) to quantify submission risk, build risk registers, track mitigations, and emit standardized R4SUB evidence rows.

It answers the question:

What are the key risks to submission readiness, how severe are they, and are they being addressed?

Core Concepts

FMEA Risk Model

Each risk is scored on three dimensions (1--5 scale):

• Probability: likelihood the issue persists to submission
• Impact: regulatory consequence if unresolved
• Detectability: difficulty of catching the issue (1=easy, 5=hard)

RPN (Risk Priority Number) = Probability x Impact x Detectability (range 1--125)

RPN Bands

Installation

pak::pak(c("R4SUB/r4subcore", "R4SUB/r4subrisk"))

Quick Start

library(r4subcore)
library(r4subrisk)

# From a manual risk register
risks <- data.frame(
  risk_id       = c("R001", "R002"),
  description   = c("Missing SDTM variables", "Unmapped ADaM derivations"),
  category      = c("data_quality", "traceability"),
  probability   = c(4, 3),
  impact        = c(5, 4),
  detectability = c(2, 3)
)
rr <- create_risk_register(risks)
rr

# Or derive risks automatically from evidence
risk_items <- evidence_to_risks(evidence)
rr <- create_risk_register(risk_items)

# Compute scores and emit evidence
scores <- compute_risk_scores(rr)
ctx <- r4sub_run_context(study_id = "ABC123", environment = "DEV")
ev <- risk_register_to_evidence(rr, ctx = ctx)

Core Functions

Design Principles

• FMEA-grounded: industry-standard risk methodology
• Evidence-first: all risk items emit r4subcore evidence rows
• Mitigation-aware: track and measure risk reduction over time
• Transparent: every RPN is decomposable into P x I x D

License

MIT