MAFI - Mapping Pharma Mechanistic Vulnerabilities

MDDR

Inside a MAFI Assessment

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Mechanistic intelligence for pharmaceutical and biotechnology decision-making.MAFI decomposes a therapeutic programme into its mechanistic dependencies, assesses each for fragility, and benchmarks them against comparable programmes.<h3>Mechanism → Dependencies → Fragility → Intelligence</h3>

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MAFI

Early identification of strategic risks within drug mechanisms to aid in risk management and development planning.

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Strategic Risk Identification

Detailed analysis and mapping of dependencies within pharmaceutical and biotech mechanisms to uncover critical points of vulnerability.

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Mechanism Dependency Mapping

Assessment of concentration and distribution of dependencies to understand the architecture and resilience of mechanisms.

Concentration Analysis

Identification and evaluation of fragility within biological mechanisms to highlight potential risks and intervention points.

Fragility Assessment

Assesses a programme's mechanism in absolute terms — what it depends on, how fragile those dependencies are, and where failure would originate.

MDDR 

Positions that profile against comparable programmes — how the programme's architecture, domain scores, and overall fragility compare to its peers.

Reports

A comparative assessment of a therapeutic programme's mechanistic profile — how its dependency burden, architecture, and fragility compare to comparable programmes, and what that position implies.The Mechanistic Benchmarking Report (MBR) positions a programme's mechanistic profile relative to defined reference populations. It draws on the same dependency decomposition and fragility assessment that underpins the Mechanistic Due Diligence Report, but applies them comparatively — asking not only what is this programme dependent on? but how does that profile compare to comparable programmes, and where does it sit within the distribution?The MBR benchmarks four dimensions: dependency burden (how many dependencies the programme carries), dependency architecture (how those dependencies are distributed across layers and centrality classifications), fragility domain distribution (how the programme scores across the five fragility domains), and integrated fragility distribution (how many dependencies resolve as Robust, Conditional, or Brittle). Each dimension is benchmarked against nested reference populations, with outcome-stratified comparison providing the primary interpretive context.The MBR is a comparative product. It does not predict outcome. It describes where a programme sits relative to comparable programmes, and whether its profile resembles the profiles associated with success or failure in similar development contexts.

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A structured assessment of a therapeutic programme's mechanistic dependencies — where the mechanism is fragile, and where failure is most likely to originate.The Mechanistic Due Diligence Report (MDDR) decomposes a programme's claimed mechanism of action into its individual mechanistic dependencies — the independently falsifiable propositions upon which the therapeutic thesis rests. Each dependency is assessed across five fragility domains, integrated into a fragility tier, and evaluated for centrality. The result is a structured view of where the mechanism is robust, where it is fragile, and which dependencies represent the programme's most consequential points of potential failure.The MDDR is a diagnostic assessment. It does not predict outcome. It identifies the conditions that must hold for the mechanism to succeed, and the points at which those conditions are most likely to break down.

A complete MDDR contains:Programme Metadata — The programme's identity, mechanism of action, target, modality, and development stage.Claimed Mechanism of Action — A reconstruction of the programme's biological rationale, from publicly available sources.Dependency Inventory — A complete list of the mechanistic dependencies identified through structured decomposition of the claimed mechanism.Dependency Architecture — A structural view of how those dependencies are distributed across biological, translational, clinical, and strategic layers, and how they are classified by centrality.Fragility Assessment — A domain-by-domain assessment of each dependency, with integrated fragility tiers.Critical Failure Nodes — The dependencies whose failure would produce the greatest adverse effect on the claimed mechanism, identified by combining centrality and fragility.Mechanistic Pre-Mortem Failure Cascade — A structured stress test that traces how failure at a critical dependency would propagate through the programme's architecture to clinical and programme-level consequences.Historical Mechanistic Analysis — Comparison with historical programmes that relied on analogous mechanistic dependencies, providing contextual precedent.

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A complete MBR contains:Programme Metadata — The programme's identity, mechanism of action, target, modality, and development stage.Dependency Profile — The programme's dependency inventory, as assessed in the underlying MDDR framework.Reference Population Definitions — The nested reference populations used for benchmarking: the MAFI database, the therapeutic area, the modality, the comparable cohort, and the outcome-stratified comparable cohorts.Dependency Burden Benchmark — The programme's total dependency count, positioned against the distribution of dependency counts within each reference population.Dependency Architecture Benchmark — The distribution of the programme's dependencies across layers and centrality classifications, compared against reference population distributions.Fragility Domain Benchmark — The programme's domain-level score distributions, compared against reference populations for each of the five fragility domains.Integrated Fragility Benchmark — The programme's distribution across Robust, Conditional, and Brittle tiers, compared against reference populations and against outcome-stratified cohorts.Critical Dependency Convergence — For each of the programme's critical dependencies, an analysis of whether the same fragility configuration has occurred historically within the database, and how matched programmes were distributed across successful and failed outcomes.

A structured method for assessing the mechanistic robustness of therapeutic development programmes.<h4>What The Framework Is</h4>MAFI (Mechanistic Architecture Fragility Intelligence) is a framework for evaluating the mechanistic dependencies that underpin a therapeutic programme's claimed mechanism of action. It decomposes that mechanism into independently falsifiable assumptions, assesses each assumption across five fragility domains, and integrates the domain scores into a fragility tier. The result is a structured view of where a mechanism is robust, where it is fragile, and where failure is most likely to originate.The framework is rule-based, not judgement-based. Every classification is derived from explicit criteria, and every assessment is traceable to the evidence that supports it. This makes MAFI reproducible — two trained analysts applying the framework to the same programme should reach the same conclusions.<h4>How It Works</h4>The framework proceeds through six analytical stages.1. Mechanism Reconstruction The programme's claimed mechanism of action is reconstructed from publicly available scientific and regulatory evidence. This establishes the therapeutic thesis that the assessment will evaluate.2. Dependency Decomposition The mechanism is decomposed into its individual mechanistic dependencies — the independently falsifiable assumptions upon which the therapeutic thesis rests. Each dependency is a distinct condition that must hold for the mechanism to succeed.3. Dependency Architecture Each dependency is classified by layer — Biological, Translational, Clinical, or Strategic — and by centrality — Core or Peripheral. This establishes where the dependency operates and how essential it is to the programme's mechanism.4. Fragility Assessment Each dependency is assessed across five fragility domains: Evidence Proximity, Context Dependence, Historical Failure Prevalence, Recoverability, and Earliest Detectable Phase. Domain scores are integrated into a fragility tier — Robust, Conditional, or Brittle.5. Critical Failure Node Identification Dependencies whose failure would produce the greatest adverse effect on the claimed mechanism are identified by combining centrality and fragility. These are the points at which the mechanistic chain is most vulnerable.6. Benchmarking and Convergence The programme's dependency profile is positioned against defined reference populations, with outcome-stratified comparison providing interpretive context. Critical dependency configurations are matched against historical precedent to identify whether similar patterns have occurred before.<h4>The Fragility Domains</h4>Each dependency is assessed across five fragility domains.Evidence Proximity measures how directly an assumption is supported by relevant evidence. High Evidence Proximity means direct human evidence; Low means support is primarily inferential or preclinical.Context Dependence measures how broadly an assumption is expected to remain valid across patient populations, disease stages, and treatment settings. High Context Dependence means the assumption may fail when conditions vary.Historical Failure Prevalence measures how frequently comparable assumption classes have historically broken down across therapeutic development. High means the assumption class has a well-established history of failure.Recoverability measures whether a programme can realistically recover from assumption failure while preserving its core therapeutic thesis. Low Recoverability means failure invalidates the mechanism.Earliest Detectable Phase measures the earliest stage at which assumption failure could be detected with sufficient confidence to materially challenge the programme. It ranges from Preclinical to Post-Approval.<h4>The Principles</h4>The framework is governed by four principles.Prospective, not retrospective. Assumptions are identified from the programme's original therapeutic rationale, not from later events. A programme's outcome — success or failure — does not influence the classification of its assumptions.Rule-based, not judgement-based. Every classification is derived from explicit criteria. Domain scores are integrated into fragility tiers using defined rules, not analyst discretion. This makes the framework reproducible.Comparative, not predictive. The framework describes where a programme sits relative to comparable programmes. It does not predict outcome. A programme with a fragile profile may still succeed; a programme with a robust profile may still fail.Evidence-anchored. Every classification is traceable to the evidence that supports it. The framework's outputs are auditable, and its assessments can be challenged on evidential grounds.The framework described above is applied consistently across every MAFI assessment. Its classification rules, integration logic, and evidence standards are documented in full in the MAFI Ontology, which is available on request. The ontology is the reference specification for the framework; the reports are its application to individual programmes.

The MAFI Framework

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Critical Failure NodesThe MDDR identifies not just which dependencies are fragile, but which fragile dependencies matter most. By combining centrality and fragility, it isolates the dependencies whose failure would fundamentally undermine the therapeutic thesis — the points at which the mechanistic chain is most vulnerable.For Ganetespib, this analysis identified four critical dependencies concentrated in the Biological layer, forming a sequential chain from tumour-cell dependence on HSP90 client proteins through to the persistence of the antitumour effect in the presence of resistance mechanisms.Mechanistic Pre-Mortem Failure CascadeThe pre-mortem assumes the principal critical failure node does not hold, and traces the consequences through the programme's dependency architecture — from mechanistic disruption, through biological consequence, to translational and clinical failure.This converts a static assessment into a dynamic model of how failure could propagate. It is the analytical payoff of the framework.Dependency ArchitectureThe MDDR maps the mechanism as a dependency structure — not as a narrative, not as a list of risks, but as a layered architecture with defined nodes and centrality classifications.This visual is often the first thing a reader understands about the framework: that mechanism is a chain, and the chain has weak links.

Outcome-Stratified BenchmarkingThe MBR benchmarks a programme's profile separately against successful and failed comparable programmes. This allows the programme's mechanistic characteristics to be interpreted against the profiles associated with each outcome, without collapsing outcome into a single reference.For Ganetespib, the programme's dependency burden exceeds the median of both successful and failed comparable programmes — by 37.5% and 57.1% respectively. This is a non-obvious finding: the programme is not just elevated relative to its peers, it is structurally anomalous even among failures.Integrated Fragility DistributionThe MBR positions a programme's distribution across fragility tiers against reference populations. This is the summary measure of programme fragility, and it is often the most discriminating benchmark.Ganetespib has no Robust dependencies — compared with approximately 10% Robust dependencies among successful comparable programmes. Its 36.4% Brittle proportion aligns more closely with the failed comparable cohort (37.9%) than the successful comparable cohort (21.9%).Critical Dependency ConvergenceFor each of the programme's critical dependencies, the MBR identifies whether the same fragility configuration has historical precedent within the database, and how matched programmes were distributed across outcomes.This is the bridge from description to positioning. It converts the framework from a static assessment into a comparative instrument — showing not just where the programme sits, but whether its critical configurations have been seen before, and with what results.

Mechanistic Dependency Burden by OutcomeGanetespib's dependency burden exceeds the median of both successful and failed comparable programmes — by 37.5% and 57.1% respectively

Mechanistic Pre-Mortem Failure CascadeThe cascade traces how failure at Ganetespib's principal critical dependency — the emergence of resistance before sustained tumour control is achieved — would propagate through the programme's mechanistic architecture.

Inside a MAFI AssessmentWhat follows is a walkthrough of a MAFI assessment, using Ganetespib — an HSP90 inhibitor developed for advanced non-small cell lung cancer — as the demonstration case.MAFI's assessment found a programme whose mechanism is structurally fragile across multiple layers. Ganetespib carries no Robust dependencies, concentrates its critical failure points in the biological layer, and positions more closely to failed comparable programmes than successful ones.The walkthrough draws on two report types. The MDDR assesses a programme's mechanism in absolute terms. The MBR positions that profile against comparable programmes.The six panels that follow move from the programme's dependency architecture, through its fragility assessment and critical failure points, to its comparative position against reference populations. Each panel shows an actual output from the Ganetespib reports, with a short interpretation of what it found.

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Monitoring and reporting emerging trends in pharma and biotech mechanisms that could impact dependency structures.

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Pharma Trend Intelligence

Interactive sessions designed to map and visualize dependencies within pharmaceutical mechanisms, helping teams identify critical points of failure.

Dependency Mapping Workshops

Detailed analysis pinpointing areas where risk is concentrated within a mechanism, enabling proactive mitigation strategies.

Risk Concentration Analysis

Dependency ArchitectureMechanistic Due Diligence ReportGanetespib's dependencies are disproportionately concentrated in Core classifications, with zero Peripheral Biological dependencies. Every biological assumption the programme makes is treated as core to the mechanism.Finding: Core concentration at 63.6%, zero Peripheral Biological. Implication: Every biological assumption is core.

Fragility AssessmentMechanistic Due Diligence ReportGanetespib has no Robust dependencies. Four of its eleven dependencies resolve as Brittle; the remaining seven as Conditional. The mechanism carries no assumption that meets the criteria for well-supported, context-independent resilience.Finding: No Robust dependencies; four Brittle, seven Conditional. Implication: No assumption meets the Robust criteria.

Critical Failure NodesMechanistic Due Diligence ReportGanetespib's four Critical Failure Nodes are concentrated in the Biological layer and form a sequential chain — from tumour-cell dependence on HSP90 client proteins through to the persistence of the antitumour effect in the presence of resistance mechanisms. The most consequential points of failure lie in the biology itself.Finding: Four Critical Failure Nodes, Biological layer, sequential chain. Implication: The most consequential failure points are biological.

Mechanistic Due Diligence Report

Utilize computational models to simulate disruptions in mechanisms and predict potential outcomes and cascading effects.

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Mechanism Disruption Simulation

Visualize and map out complex dependency relationships within biological mechanisms to reveal hidden points of failure.

Dependency Network Mapping

Analyze and compare the mechanistic dependencies of competing pharma and biotech entities to identify unique vulnerabilities and strengths.

Competitive Mechanism Benchmarking

Dependency Layer Distribution by Comparison GroupMechanistic Benchmarking ReportGanetespib's dependency architecture is unusually weighted toward Translational assumptions — 36.4% of its dependencies sit in the Translational layer, the highest proportion across all six reference populations. Its Biological proportion is correspondingly depressed at 36.4%, the lowest across all comparison groups. The programme carries far more of its mechanistic burden in translation than its peers.Finding: 36.4% Translational (highest across all reference populations); 36.4% Biological (lowest across all comparison groups).Implication: The programme carries far more of its mechanistic burden in translation than its peers.

Historical Failure PrevalenceMechanistic Benchmarking Report45.5% of Ganetespib's dependencies fall within the High Historical Failure Prevalence tier — more than twice the comparable cohort's 17.4% — and none fall within the Low tier. The programme's dependency classes are disproportionately drawn from those with an established history of failure.Finding: 45.5% High; 0% Low. Implication: Dependency classes drawn from historically failure-prone categories.

Integrated FragilityMechanistic Benchmarking ReportGanetespib has no Robust dependencies, compared with approximately 10% among successful comparable programmes. Its 36.4% Brittle proportion aligns more closely with the failed comparable cohort (37.9%) than the successful comparable cohort (21.9%). The programme's overall fragility profile resembles the profiles associated with failure more closely than those associated with success.Finding: No Robust; 36.4% Brittle. Implication: Profile resembles failed comparables more than successful ones.

Mechanistic Benchmarking Report

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MAFI

Mechanism → Dependencies → Fragility → Intelligence

Reports

MDDR

MBR

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