EBICap
EBICAPEvidence‑Based Investing · Capital

Data Architecture

How We Build the Score

Six public data sources feed five analytical pillars. Pillar scores are composite-weighted then peer-adjusted — producing a single, comparable Clinical Value Score (0–100) for every covered company.

DATA SOURCES
PILLAR PROCESSING
AGGREGATION
OUTPUT

Hover any node for detail · particles show live data flow

Clinical Benefit

Translates benefit ratings into a calibrated clinical value signal per therapeutic context.

Pipeline Activity

Breadth, quality, and phase progression of each company's active development portfolio.

Capital Governance

Executive incentive alignment, capital deployment, and board composition scoring.

Burden Alignment

Overlap between a company's pipeline and highest-burden disease categories globally.

Research Integrity

First-in-class ratio, publication quality, and research-commercial separation scores.

Therapeutic Clusters

Groups companies by therapeutic focus for like-for-like peer comparisons.

All data sourced from primary public registries · scores recomputed quarterly for 676 companies

Key Findings

77%

of new medicines 2010–2019 offer no or only slight improvement over existing treatments

EbiCap analysis · PMPRB data · n=390

About

EbiCap — Pharmaceutical Value & Society

EbiCap is an independent research platform that asks one question: do pharmaceutical companies generate clinical value for society proportional to the financial capital they extract from it?

We aggregate and analyse data from global regulatory bodies, clinical trial registries, and public health institutions to produce the Therapeutic Impact (TF) Score — a multi-dimensional ranking system covering 633 publicly listed pharmaceutical companies. Every metric is derived automatically from primary public sources with no analyst subjectivity and no paid data feeds.

The question is deceptively simple: does each drug actually improve health outcomes relative to what already exists — and is its price proportionate to that benefit?

⚖️

Mission

Make the relationship between pharmaceutical R&D investment, clinical benefit, and public health outcomes legible, measurable, and comparable across every major company.

🔬

Approach

Automated, reproducible pipelines built on globally recognised public health and regulatory data — rebuilt continuously, with full audit trails from source to score.

🛡️

Independence

No pharma industry funding. No proprietary data access. Every number in the platform can be traced to a primary public source, ensuring complete objectivity.

🌍

Purpose

Support payers, policymakers, investors, and patient advocates in evaluating whether capital allocated to pharmaceutical R&D serves the populations most in need.

633
Companies analysed
350k+
Clinical trials indexed
10+
Years of financial data

The Evidence Problem

The Evidence Problem — Publication Bias

A well-documented structural problem in pharmaceutical research is selective publication: companies run many trials but negative results are roughly twice as likely to remain unpublished as positive results — creating a systematically distorted evidence base.

The consequences reach every prescribing decision. Guideline authors, health technology assessment bodies, and physicians are working from an incomplete picture. A drug that appears effective in the published literature may have a very different benefit–risk profile when negative results are seen.

~50%

Publication bias risk

Estimated proportion of negative trial results never published

<40%

WHO mandate compliance

Proportion of clinical trials that meet the 1-year WHO publication deadline (AllTrials)

~30%

Outcome switching rate

Frequency of primary endpoint changes between registration and publication (Chan et al. 2004)

EbiCap tracks publication rates and outcome consistency for registered trials. Companies where completed trials produce no published results — or where published endpoints differ from registered endpoints — receive a reduced trial transparency sub-score in P2.

Source: Bourgeois FT et al. (2010) NEJM; Chan AW et al. (2004) JAMA; WHO Trial Registration Network.

What Real Innovation Looks Like

What Real Innovation Looks Like — Le Fanu's Timeline

James Le Fanu's The Rise and Fall of Modern Medicine (1999) charted the twelve definitive advances in twentieth-century medicine — the interventions that genuinely transformed the human condition. His timeline reveals a striking pattern: genuine breakthroughs cluster in short windows; they are almost never incremental.

Breakthrough Eras (Le Fanu Framework)

1940–1965

Antibiotic & Steroid Revolution

Penicillin (1943), streptomycin (1947), cortisone (1948), polio vaccine (1955), chlorpromazine (1952)

1970–1995

Chronic Disease Era

ACE inhibitors (1981), statins (1987), H₂ blockers (1976), beta-blockers, SSRIs — diseases managed across decades

1995–2005

Biotech Transition

Anti-TNF biologics (rheumatoid arthritis 1998), imatinib for CML (2001), HAART for HIV (1996)

2006–present

Incremental Accumulation

Predominantly me-too compounds, formulation changes, new indications for existing molecules; genuine breakthroughs rare and costly

Modern pharmaceutical companies predominantly operate in the fourth era — producing compounds that offer marginal improvements within already-crowded therapeutic classes, while pricing them as if they were transformative. EbiCap's innovation tier system traces this pattern at company level.

The QALY Standard

The QALY Standard — What Real Value Looks Like

Canada's Patented Medicine Prices Review Board (PMPRB) introduced a five-level “therapeutic improvement” scale that maps each benefit rating onto an empirically derived QALY gain per patient per year. This provides a concrete answer to the question: what does “added benefit” actually mean in terms of healthy life?

Benefit LevelQALY GainHealthy DaysTypical Example
0 — No added benefit0.003~1 dayIncremental dose change, no clinical difference
1 — Minor improvement0.055~20 daysModest symptomatic relief vs existing therapy
2 — Moderate improvement0.126~46 daysMeaningful reduction in disease burden
3 — Substantial improvement0.307~112 daysMajor clinical advance (e.g. first TNF inhibitor 2000)
4 — Major improvement / Breakthrough0.683~249 daysFirst effective treatment for a serious condition

EbiCap uses this scale as the primary unit of measurement for P1 (Clinical Benefit). The score is normalised against 0.683 QALYs — the value of a genuine breakthrough.

The Independence Standard

The Independence Standard — The Mario Negri Model

Donald Light and Antonio Maturo's Good Pharma (2015) profiles the Istituto di Ricerche Farmacologiche Mario Negri in Milan as the benchmark for what genuinely independent pharmaceutical research looks like. The Mario Negri Institute (MNI) runs trials with:

Pre-registration

All trials registered before recruitment begins, with protocol locked

Active comparator

Best existing therapy always used as comparator — never placebo alone

Clinical endpoints

Outcomes patients care about: mortality, hospitalisation, quality of life

Full publication

All results published regardless of direction — positive and negative

All-cause mortality

Primary endpoint includes all deaths, not just disease-specific deaths

Open data

Data shared with other researchers on request, with patient consent

Industry-sponsored trials routinely fall short on several dimensions. Choosing placebo comparators inflates apparent efficacy. Surrogate endpoint selection enables regulatory approval without confirming patient benefit. Selective publication hides harms. The Mario Negri benchmark makes each gap visible.

The Innovation Gap

The Innovation Gap — 4,000 Diseases, 250 Treated

Of the approximately 4,000 diseases with known causes, effective treatments exist for roughly 250. The remaining 3,750 represent an investment gap — conditions where the global disease burden is real but the commercial incentive is insufficient to attract industry capital. This gap is structural, not accidental.

~4,000

Diseases with known cause

~250

With effective treatments

~3,750

Without adequate treatments

The concentration of pharmaceutical investment in high-revenue therapeutic areas — oncology, immunology, neurology in wealthy markets — leaves conditions affecting billions of people in lower-income countries systematically neglected. EbiCap's disease burden alignment score (P4) rewards companies that actively build pipelines in high-burden, low-commercial-incentive areas.

Executive Incentive Quality

Executive Incentive Quality — VCSi Regressions

EbiCap classifies executive incentive structures across pharmaceutical companies into three regimes: VCSi (Value-Creating Science incentives) link executive pay to patient outcomes, clinical milestones or societal benefit metrics. VCShi link to softer health-science proxies. Financial-only link exclusively to TSR, EPS and revenue growth.

Crucially, the regime a company adopts is not permanent. EbiCap tracks year-by-year changes. Companies that downgrade from VCSi to weaker types — “regressions” — signal a retreat from patient-value orientation. Notable examples:

Eisai2020
VCSiVCShi

Downgraded patient-outcome triggers to softer health-science indicators

GlaxoSmithKline2019
VCSiFinancial

Restructured exec comp towards TSR metrics following biopharma split

Novartis2018
FinancialVCSi

First major pharma to link CEO pay to access & innovation KPIs

Novo Nordisk2021
VCShiVCSi

Embedded patient-affordability metrics into LTIP after PCSK9 pricing controversy

The Regulatory Gap

The Regulatory Gap — Health as the Missing ESG Spoke

The EU Sustainable Finance Disclosure Regulation (SFDR) and EU Taxonomy (Regulation 2019/2089) define rigorous disclosure and classification standards for environmental and social factors — including climate transition plans with science-based targets. Yet no equivalent framework exists for health outcomes as a dimension of investor accountability.

The ESG Taxonomy Gap

Environmental

Science-based targets · EU Taxonomy aligned · TCFD reporting

Social

Partial (labour rights, gender diversity); no health-output mandate

Health

No benchmark. No science-based target. No EU Taxonomy definition.

The WHO's ESG+H proposal (2022) called for the inclusion of health outcomes as a formal fourth pillar of ESG investor reporting, with mandatory disclosure of the clinical benefit delivered by investee pharmaceutical companies. PGGM's policy language — requiring portfolio companies to demonstrate therapeutic improvement over existing treatments — represents the current gold standard for investor health policy.

PGGM Responsible Investment Framework — Health Policy Approach (2021):

Portfolio pharmaceutical companies are expected to demonstrate that new products provide clinically meaningful improvement over existing treatments as assessed by an independent health technology assessment body. Companies that systematically fail this standard are subject to escalation through engagement, voting and, ultimately, divestment.

Paraphrased from PGGM Responsible Investment Policy (2021 edition). The underlying expectation — requiring evidence of added value vs. existing treatments assessed by an independent body — is documented in PGGM’s published policies.

The EbiCap Therapeutic Impact framework was built specifically to operationalise this standard at scale. A company's TF Score is a direct, evidence-based answer to the question institutional investors increasingly ask: does this company’s pipeline deliver meaningful clinical benefit over existing treatments?

Methodology

Our Research Framework

The EbiCap Therapeutic Impact framework is built on a single conviction: that the value a pharmaceutical company delivers to society can be measured objectively, without relying on self-reported metrics, marketing claims, or subjective analyst opinion.

The Five Pillars

P1

Clinical Benefit & Access

HTA ratings from NICE, G-BA/IQWiG, HAS and PMPRB mapped onto a QALY ladder. Primary signal — what benefit do patients actually receive, relative to existing treatments, and at what cost of access?

P2

Pipeline Quality & Innovation

Quality and composition of each company's active clinical pipeline — not size. Pipelines targeting genuine unmet needs, carrying regulatory designations evidencing meaningful improvement, score higher than expansive pipelines of incremental or copycat compounds. Trial transparency sub-score for publication rate and active comparator usage.

P3

Capital Stewardship

How companies deploy the capital they generate — measuring the balance between reinvestment into research and extraction via shareholder payouts. Executive compensation structures for alignment with patient outcomes vs. short-term financial metrics (VCSi/VCShi taxonomy).

P4

Disease Burden Alignment

Strategic alignment with true unmet need, measured against globally recognised GBD 2023 disease burden data. Companies targeting high-DALY, high-severity, high-unmet-need conditions score highest.

P5

Efficiency & Governance

How efficiently research investment translates into output, with an Angell discount for companies whose approved drugs extensively cite NIH-funded public research — reducing private R&D efficiency credit when foundational science was taxpayer-funded.

Advanced Model Layerv3.3 — Post-composite adjustment

Mean Field Peer-Adjustment

Pharmaceutical companies do not operate in isolation. Their compensation structures, R&D priorities, and regulatory risk profiles are correlated through shared institutional ownership and competitive pressure within therapeutic areas. A scoring model that treats each company as independent ignores this fundamental structure.

EbiCap incorporates a Mean Field Peer-Adjustment — a concept borrowed from statistical physics, where the state of each particle in a complex system is influenced by the average behaviour of all other particles (the “mean field”). Applied to pharmaceutical accountability:

Layer 1 — Therapeutic Cluster Field

Companies are assigned to one of 17 ICD-10 chapter clusters based on the plurality of their registered trial conditions (e.g. C=Oncology, G=Neurology, F=Mental Health, I=Cardiovascular). Each company's raw TF Score is normalised against its cluster's mean and standard deviation — a company scoring 2σ above its oncology peers is assessed differently than one scoring 2σ above in a smaller, weaker cluster.

Layer 2 — Ownership Network Field

Using SEC 13-F institutional holdings, we compute an AUM-weighted ownership overlap matrix. The ownership field for each company is the share-weighted mean z-score of its institutional co-owners' other portfolio companies. Being predominantly owned by funds that tolerate poor governance at peer companies represents systemic ecosystem risk — captured here.

The Result

A company 2σ above its therapeutic peers, owned by shareholder-engaged institutional funds, can receive up to +5 points post-composite. A company performing below its peer mean AND held by governance-indifferent funds across multiple low-accountability positions receives up to −5 points. The adjustment is bounded by the hyperbolic tangent function — it contextualises the score without overriding first-order pillar assessments.

For

Who Uses EbiCap

ESG & Responsible Investment

Screen pharma holdings for genuine patient-outcome orientation vs. value extraction. Verify PGGM-standard therapeutic improvement. Flag VCShi compensation before the next governance scandal. Audit SLB health KPIs.

Healthcare Hedge Funds

Access differentiated alpha signals: HTA clinical benefit vs. market pricing, first-in-class pipeline quality, institutional ownership overlap, and MFT peer-relative score deviations that precede re-rating events.

Pension Funds & SLB Issuers

Assess and monitor health-linked KPI commitments on Sustainability-Linked Bonds. Track real clinical outcome delivery against bond covenant targets using EbiCap’s independent HTA-grounded scoring.

Policy & Advocacy

Quantify the gap between R&D capital deployment and therapeutic need for cite-ready advocacy. Neglect Index, economic welfare values (Murphy & Topel), and DALY/trial count ratios — all with full source citations.

Investigative Journalists

Cross-link 12 public datasets in one query. Settlement history, physician payments, HTA rejections, patent transfers, and executive comp triggers — the data infrastructure for accountability reporting.

HTA Bodies & Payers

Benchmark company-level transparency, trial quality, and disease-burden alignment. Use EbiCap as an independent academic reference when negotiating reimbursement or coverage conditions.

Health Ministries

Inform drug reimbursement decisions with comparative data on therapeutic value, patent lifecycle, pricing disparity, and clinical pipeline quality — across the entire marketed pharmaceutical universe.

Pharma Executives

Benchmark your company against peers and the full industry on TF Score pillars. Understand where capital deployment, pipeline composition, and compensation structure compare against best-in-class and sector mean field.