---
title: >-
  Orthogonalized Regression for Causal Inference: A Pharmacoepidemiologist's
  Dream?
description: >-
  Explore this publication on real-world evidence: Orthogonalized Regression for
  Causal Inference: A Pharmacoepidemiologist’s Dream?.
date: '2023-01-01'
author: Nuvan Rathnayaka
category: Publications
tags:
  - ICPE
  - Approval & Commercialization
  - 'Yes'
  - Oral Presentation
  - Methods/Pharmacoepi
  - R&D
canonical_url: >-
  https://www.headwaterscience.com/resources/publications/icpe/orthogonalized-regression-for-causal-inference-a/
source: Headwater Science
license: © 2026 Headwater Science. All rights reserved.
slug: orthogonalized-regression-for-causal-inference-a
id: Y3YO8B5RD2KEu84yoMHcN
contentType: article
---

## Challenge

Orthogonalized regression methods had emerged in statistics and machine learning but had not been evaluated from a pharmacoepidemiologist's perspective for applicability to standard drug effectiveness questions.

## Solution

Target RWE researchers presented an oral critical evaluation of orthogonalized regression for causal inference in pharmacoepidemiology settings, assessing its advantages, limitations, and practical conditions under which it outperforms or underperforms standard propensity score methods.

## Impact

Critically evaluating emerging causal inference methods positions Target RWE as a rigorous and discerning methodologist, building pharma partner and regulatory confidence in the company's analytic decision-making.

## Use Cases / Links

Critical evaluation of orthogonalized regression for causal inference in pharmacoepidemiology applications, Emerging statistical method assessment for applicability to pharma partner drug effectiveness programs