ClinicalIntelPulse Clinical Trial Failure Analysis

x402

ClinicalIntelPulse Clinical Trial Failure Analysis is a paid API for AI agents from clinicalintelpulse.theaslangroupllc.com, paid per call via x402, $0.2/call, status unknown (last checked 2026-09-14).

Returns a structured failure taxonomy for Phase 2/3 clinical trials in a disease area, including failure reasons, percentages, phase-transition success rates, and design lessons.

Price / call$0.2

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How this service works

Clinical trial failure analysis for a disease area — why Phase 2/3 trials failed (wrong target, patient population, endpoint, dose, safety), failure taxonomy with percentages, phase-transition success rates and design lessons. Worldwide. For drug developers and biotech investors.

Output

A structured failure taxonomy for Phase 2/3 trials in the queried disease area, including categorized failure reasons (wrong target, patient population mismatch, endpoint failure, dose issues, safety signals), percentage breakdowns across categories, historical phase-transition success rates, and actionable design lessons for drug developers and biotech investors.

Example use cases

Alzheimer's drug trial risk assessment

“We're considering investing in an early-stage Alzheimer's biotech. Can you pull the failure taxonomy for Phase 2 and Phase 3 trials in that space — what percentage fail on endpoints versus patient population mismatches, and what are the phase-transition success rates? I need to understand the biggest risks.”

NASH trial design optimization before IND

“Our team is designing a Phase 2 NASH trial and we want to avoid common pitfalls. What does the failure data show — are most NASH trials failing on wrong endpoints, wrong patient populations, or safety signals? And what's the success rate getting from Phase 2 to Phase 3?”

Rare disease phase-transition benchmarking

“We have a rare autoimmune indication and need to benchmark our phase-transition assumptions. What are the historical success rates moving from Phase 2 to Phase 3 in autoimmune diseases, and what are the top three reasons trials fail at each stage? We want to reality-check our go/no-go criteria.”

Technical details

Endpoint

GEThttps://clinicalintelpulse.theaslangroupllc.com/api/clinical/failure-analysis

When to prefer

Use this endpoint when you need structured, quantitative intelligence on why clinical trials fail in a specific disease area — particularly for informing trial design decisions, go/no-go investment assessments, or competitive risk benchmarking. Prefer this over general pipeline endpoints when the core question is root-cause analysis of trial failure rather than active pipeline status or approval probability.

Side effects

Unknown or unsupported disease area returns empty or error response
Overly broad disease category may return low-confidence aggregated data
Rate limiting or payment failure if USDC balance is insufficient
Network timeout for complex or data-sparse disease areas

Input

Schema · Request body

Field	Type	Description
inputrequired	object
output	object

Output

Schema · Response

{
  "type": "json",
  "example": {
    "query_summary": {
      "condition": "Alzheimer Disease",
      "trials_analyzed": 78
    },
    "lessons_learned": [
      "Early intervention is critical — treat pre-symptomatic or MCI only",
      "Amyloid PET and CSF biomarkers required for enrollment (not just clinical diagnosis)",
      "CDR-SB global score now accepted primary endpoint by FDA (post-2018)",
      "ARIA management protocols must be pre-specified — not post-hoc",
      "Combination approaches (amyloid + tau + neuroinflammation) likely needed"
    ],
    "failure_taxonomy": {
      "wrong_endpoint": {
        "pct": 18,
        "examples": [
          "ADAS-Cog and MMSE insensitive to early disease changes; CDR-SB now standard"
        ],
        "key_trials": [
          "Multiple agents 2010-2020"
        ]
      },
      "safety_termination": {
        "pct": 8,
        "examples": [
          "ARIA (amyloid-related imaging abnormalities) from anti-amyloid antibodies; dose-limiting"
        ],
        "key_trials": [
          "Aducanumab Phase 3 dose arm"
        ]
      },
      "operational_failures": {
        "pct": 4,
        "examples": [
          "COVID-19 disruption, enrollment failures in rare AD subpopulations"
        ]
      },
      "wrong_patient_population": {
        "pct": 28,
        "examples": [
          "Treating symptomatic patients too late — amyloid deposited 10-15 years before symptoms"
        ],
        "key_trials": [
          "Bapineuzumab (mild-moderate vs. early)"
        ]
      },
      "wrong_target_or_hypothesis": {
        "pct": 42,
        "examples": [
          "Decades of amyloid-only focus; tau, neuroinflammation, synaptic loss all contributing to failure cascade"
        ],
        "key_trials": [
          "Solanezumab",
          "Verubecestat",
          "Atabecestat"
        ]
      }
    },
    "what_still_might_fail": [
      "Tau-targeting agents if amyloid clearance alone sufficient",
      "Agents tested in wrong disease stage despite lessons",
      "CNS inflammation approaches without biomarker stratification"
    ],
    "historical_success_rates": {
      "phase2_to_phase3_pct": 31,
      "phase3_to_approval_pct": 11,
      "vs_all_diseases_benchmark": "Alzheimer's has the lowest Phase 3 success rate of any major disease category (11% vs. 58% oncology, 67% hematology)",
      "overall_clinical_success_pct": 3.4
    },
    "successful_design_principles": "CLARITY-AD (lecanemab) and TRAILBLAZER-ALZ2 (donanemab) succeeded by: earlier disease staging, biomarker-confirmed enrollment, CDR-SB endpoint, adequate duration."
  }
}

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How this service works

Output

Example use cases

Alzheimer's drug trial risk assessment

NASH trial design optimization before IND

Rare disease phase-transition benchmarking

Technical details

Endpoint

GEThttps://clinicalintelpulse.theaslangroupllc.com/api/clinical/failure-analysis

When to prefer

Side effects

Unknown or unsupported disease area returns empty or error response
Overly broad disease category may return low-confidence aggregated data
Rate limiting or payment failure if USDC balance is insufficient
Network timeout for complex or data-sparse disease areas

Input

Schema · Request body

Field	Type	Description
inputrequired	object
output	object

Output

Schema · Response

{
  "type": "json",
  "example": {
    "query_summary": {
      "condition": "Alzheimer Disease",
      "trials_analyzed": 78
    },
    "lessons_learned": [
      "Early intervention is critical — treat pre-symptomatic or MCI only",
      "Amyloid PET and CSF biomarkers required for enrollment (not just clinical diagnosis)",
      "CDR-SB global score now accepted primary endpoint by FDA (post-2018)",
      "ARIA management protocols must be pre-specified — not post-hoc",
      "Combination approaches (amyloid + tau + neuroinflammation) likely needed"
    ],
    "failure_taxonomy": {
      "wrong_endpoint": {
        "pct": 18,
        "examples": [
          "ADAS-Cog and MMSE insensitive to early disease changes; CDR-SB now standard"
        ],
        "key_trials": [
          "Multiple agents 2010-2020"
        ]
      },
      "safety_termination": {
        "pct": 8,
        "examples": [
          "ARIA (amyloid-related imaging abnormalities) from anti-amyloid antibodies; dose-limiting"
        ],
        "key_trials": [
          "Aducanumab Phase 3 dose arm"
        ]
      },
      "operational_failures": {
        "pct": 4,
        "examples": [
          "COVID-19 disruption, enrollment failures in rare AD subpopulations"
        ]
      },
      "wrong_patient_population": {
        "pct": 28,
        "examples": [
          "Treating symptomatic patients too late — amyloid deposited 10-15 years before symptoms"
        ],
        "key_trials": [
          "Bapineuzumab (mild-moderate vs. early)"
        ]
      },
      "wrong_target_or_hypothesis": {
        "pct": 42,
        "examples": [
          "Decades of amyloid-only focus; tau, neuroinflammation, synaptic loss all contributing to failure cascade"
        ],
        "key_trials": [
          "Solanezumab",
          "Verubecestat",
          "Atabecestat"
        ]
      }
    },
    "what_still_might_fail": [
      "Tau-targeting agents if amyloid clearance alone sufficient",
      "Agents tested in wrong disease stage despite lessons",
      "CNS inflammation approaches without biomarker stratification"
    ],
    "historical_success_rates": {
      "phase2_to_phase3_pct": 31,
      "phase3_to_approval_pct": 11,
      "vs_all_diseases_benchmark": "Alzheimer's has the lowest Phase 3 success rate of any major disease category (11% vs. 58% oncology, 67% hematology)",
      "overall_clinical_success_pct": 3.4
    },
    "successful_design_principles": "CLARITY-AD (lecanemab) and TRAILBLAZER-ALZ2 (donanemab) succeeded by: earlier disease staging, biomarker-confirmed enrollment, CDR-SB endpoint, adequate duration."
  }
}