Digital Solutions l Extracting deeper phenotypic and biological context.

Enriching research through artificial intelligence and machine learning.

We connect process and software data to improve productivity and efficiency from R&D through manufacturing. Our digital solutions help life sciences teams manage complex workflows with end-to-end visibility and control. Scientific software supports discovery, development, manufacturing, and clinical diagnostics. Enterprise software, data and analytics, and AI tools help digitize processes, enrich data, simplify development, streamline manufacturing, speed time to market, and improve product quality.

Danaher digital solutions unify process and software data to improve productivity, efficiency, and operational visibility across life sciences workflows.
Scientific software supports workflows from discovery and development to manufacturing and clinical diagnostics, including analysis and machine learning.
Enterprise software helps digitize processes, optimize workflows, automate data enrichment, and support more informed operational decisions.
Data and analytics solutions consolidate and contextualize multiple data sources to strengthen process knowledge and streamline manufacturing.
AI and machine learning solutions optimize products and processes, accelerate time to market, and improve product quality.

Adopting the latest innovative analytical software can increase your decision-making confidence.

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Why It Matters

Enabling Confident Decisions at Every Stage of the Therapeutic Lifecycle

Leaders can make confident decisions when data, workflows and analytics are connected from discovery through manufacturing. This reduces risk, shortens development timelines and delivers more substantial returns while helping bring new therapies to patients more quickly.

AI-powered and machine learning (ML) image analysis speeds up discovery and decision-making. It aids target identification, phenotypic screening, spatial profiling and biomarker research. By combining high-content imaging and deep visual proteomics with advanced analytics, researchers can gain deeper biological insights faster, with better reproducibility and scalability.

The life sciences companies of Danaher support these applications with our advanced AI/ML portfolio of solutions. Contact one of our experts to learn how we can help you generate insights.

Enhancing Imaging Value

High-content imaging and deep visual proteomics provide insights into biological mechanisms during drug response and translational research studies. However, drawing clear conclusions or identifying patterns during analysis can sometimes be challenging.

AI/ML image analysis tools offer several benefits:

Boost confidence and efficiency by speeding up processing times

Help clarify biological mechanisms

Uncover relationships or trends

Assist in detecting phenotypic changes

Reduce subjectivity and minimize risk

Driving Actionable Insights

Danaher Corporation

We see a way to reduce time from raw image to fully analyzed data by up to 74%.

Leica Microsystems | Aivia AI Image Analysis Software

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Danaher Corporation

We see a way to accelerate High Content Imaging 4X and enable AI-generated analysis.

Molecular Devices | IN Carta Image Analysis Software

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Danaher Corporation

We see a way to increase assay sensitivity by 50% using AI-based phenotypic classification.

Genedata | Genedata Screener

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Videos

Danaher Corporation

Innovative AI Software Solutions Driving Biomarker Research Efficiency

Learning Objectives:

Quickly and accurately segment cells using AI so you can spend less time analyzing data and more time on the biology; Leverage your expertise or automation to classify cells into different phenotypes and interactively explore them in their spatial context

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Transforming high content screening

Transforming High-Content Screening with Intelligent Imaging and AI Analysis

Learning Objectives:

Master essential high-content imaging assays from 2D phenotypic profiling to 3D imaging using patient-derived organoids; Explore the power of AI-driven analysis with IN Carta software to tackle the most challenging screening assays

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Danaher Corporation

Learn how AstraZeneca Automates Image Analysis with Deep Learning

Learning Objectives:

Learn how automated workflows enable scalable deep learning for image analysis without requiring machine learning expertise; See how deep learning-based approaches can increase mechanistic insight and assay sensitivity, in a cardiac safety profiling case study

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Additional Resources

Leica Microsystems

What’s new with AIVIA 15

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FAQs

What is AI-driven image analysis and how does it work in life sciences?

AI-driven image analysis utilizes sophisticated algorithms to examine microscopic images and extract valuable insights. In life sciences, it aids in understanding complex cellular mechanisms and processes relevant to translational research, drug discovery and development.

How does AI improve accuracy and efficiency in image analysis?

AI enhances accuracy and efficiency by eliminating the subjectivity found in manual analysis. Additionally, it assists in detecting patterns that might otherwise remain hidden or unnoticed through basic analysis.

Which imaging types can AI analyze?

AI can analyze all types of images, from brightfield to confocal images. It can also be used for nanoscale imaging, like electron transmission microscopy.

How does AI accelerate drug discovery and research?

AI is accelerating drug discovery and research in several ways. It helps with target identification, unlocks complex cellular behaviors in cell-based assays, decodes spatial dynamics in tissue samples and can even help repurpose or design new drugs.

What should be considered when using AI in regulated labs?

Concerns vary by laboratory type, but key considerations include data security, regulatory compliance, algorithm performance and validation, documentation, audit trails and addressing ethical issues related to its use.

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