Our Services :

At Data Layer Solutions, we provide cloud-based solutions designed to support biostatistics, clinical research, drug analysis, and regulatory compliance. Our expertise in SAS-powered analytics, AI-driven insights, and data management helps pharmaceutical and biotech companies streamline operations, improve decision-making, and meet industry regulations.

  • Biostatistics & Clinical Trial Analytics

Advanced statistical modelling and data analysis to optimise clinical trial outcomes, ensure regulatory compliance, and drive evidence-based decisions.

  • Pharmacovigilance & Drug Safety

AI-driven adverse event monitoring and risk assessment solutions to enhance drug safety, automate reporting, and ensure regulatory adherence.

  • Real-World Evidence (RWE) & Epidemiology

Big data analytics for post-market surveillance, patient outcomes analysis, and healthcare research, delivering valuable real-world insights.

  • Regulatory Compliance & Data Standardisation

Ensuring compliance with FDA, EMA, and ICH-GCP guidelines through automated data standardisation, submission preparation, and validation tools.

  • Predictive Analytics & AI for Drug Discovery

Leveraging machine learning and AI to accelerate biomarker discovery, patient stratification, and clinical decision support.

  • Cloud-Based Data Management & Integration

Secure, scalable SaaS platforms for managing clinical trial data, real-time analytics, and multi-source data integration with CDISC compliance.

Partner with Data Layer Solutions to revolutionise biostatistics and pharmaceutical analytics with advanced SaaS technology.

Contact us today to learn how our solutions can support your business!

Contact Us

Clinical Data Solutions

Transforming raw clinical data into actionable insights with precision and compliance for research success.

A scientist in a white lab coat and safety goggles is working in a laboratory. The scientist is interacting with a computer and a large, complex piece of lab equipment that is likely used for automated processes. There are several objects present including a cardboard box labeled 'Glass Disposal', various laboratory instruments, and a computer monitor displaying data. The lab is well-lit and organized with cabinets and shelves containing various lab supplies.
A scientist in a white lab coat and safety goggles is working in a laboratory. The scientist is interacting with a computer and a large, complex piece of lab equipment that is likely used for automated processes. There are several objects present including a cardboard box labeled 'Glass Disposal', various laboratory instruments, and a computer monitor displaying data. The lab is well-lit and organized with cabinets and shelves containing various lab supplies.
Several sheets of paper with printed tables are clipped to a bulletin board in a corridor. The papers appear to contain data or results, indicated by numerical values and columns.
Several sheets of paper with printed tables are clipped to a bulletin board in a corridor. The papers appear to contain data or results, indicated by numerical values and columns.
Regulatory Compliance

Ensuring adherence to FDA, EMA, and global standards for reliable clinical trial reporting.

Innovative Automation

Utilizing AI-driven automation to enhance efficiency and accuracy in SAS programming for clinical research.

A laboratory machine with a protective transparent cover is positioned on a counter. Next to it, a monitor is attached, and various cables are connected. The setting appears to be sterile, with a focus on technology and instrumentation.
A laboratory machine with a protective transparent cover is positioned on a counter. Next to it, a monitor is attached, and various cables are connected. The setting appears to be sterile, with a focus on technology and instrumentation.

Insights

Transforming clinical data into actionable insights with precision and compliance.

A screen displays a list of countries alongside numerical data in red and white font on a dark background. The numbers likely represent statistics such as population or cases of a specific condition. A blurred map with highlighted areas is in the background on the right.
A screen displays a list of countries alongside numerical data in red and white font on a dark background. The numbers likely represent statistics such as population or cases of a specific condition. A blurred map with highlighted areas is in the background on the right.
A computer screen displaying a coding interface with Python code related to machine learning. The code imports libraries like sklearn and deals with model metrics such as precision and recall. A classification report is shown along with a section titled 'Different meta model trained' listing various models like DT, RF, LR, and XGB. Below, there is code for tuning an XGB model using GridSearchCV.
A computer screen displaying a coding interface with Python code related to machine learning. The code imports libraries like sklearn and deals with model metrics such as precision and recall. A classification report is shown along with a section titled 'Different meta model trained' listing various models like DT, RF, LR, and XGB. Below, there is code for tuning an XGB model using GridSearchCV.
A person wearing a lab coat and safety goggles is using a microscope at a laboratory workstation. A laptop and various scientific instruments are visible on the table, displaying data and metrics.
A person wearing a lab coat and safety goggles is using a microscope at a laboratory workstation. A laptop and various scientific instruments are visible on the table, displaying data and metrics.

Contacts

Innovation

info@datalayersolutions.com, 02038382424

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