Overview

We help pharma, biotech, pharmacovigilance and CROs & CMOs to stay forefront of innovations and gain competitive edge with:

  • Digital enabled lab work
  • Data powered research and trials
  • Intelligent manufacturing and supply chain & logistics
  • Fully automated operations

Challenges

Siloed Information Management

Siloed information of entire drug lifecycle impacts regulatory and quality compliance.

Sluggish Drug Discovery

Slow drug discovery is a major hindrance to develop more new drugs for growth.

Drug Storages

Drug shortage is a result of disruptive supply chain occurred chain due to no analytics in place.

Scale Up Production

Drug production struggles to scale up for high volume manufacturing traditional processes.

International Regulations

No major update to international regulations is stopping regulators operating beyond inspections.

Traditional Clinical Trials

Traditional clinical trials are not patient-centric, and they don’t generate robust clinical data.

Who we serve

At Veltris, we help Biotechnology, Pharmaceuticals, Pharmacovigilance and Contract Research & Contract Manufacturing organizations to overcome their challenges for innovation, growth and revenue. We help in enterprise transformations with cutting-edge technology including digital, data, analytics, artificial intelligence, automation, etc.

What we serve

We offer a comprehensive design expertise to help Life Sciences to build innovative products:

  • Next-gen Clinical trial solutions design
  • Multi-disciplinary approach to life sciences product design
  • Value design engineering across biotechnology, biopharma, optronics, etc.
  • Full-fledge prototypes before production

We help Life Sciences organizations to embed design thinking into their various software:

  • Evidence based UI/UX designs
  • Clinical & laboratories operations data visualization designs
  • Intuitive content experiences with research scientists as users first approach

We help the whole value chain of Life Science in developing systems with having greater agility and interoperability:

  • Clinical trial management and clinical data analysis systems
  • Laboratory information management systems (LIMS)
  • Scientific data management systems (SDMS)
  • Drug safety information management systems
  • Workflow management systems
  • Digital quality management systems (DQMS)

We help life sciences organizations in pioneering new discoveries with power of cloud:

  • Data collection through cloud for easy regulatory clearance
  • Centralized document management for streamline research
  • Enterprise level collaboration and use of advanced instruments
  • Seamless data integration from regulators, distributors, etc.
  • Cloud-based, digitized supply chain management

 

With next-gen tech stack, we help life sciences organizations deliver lifesaving products faster to the market.

  • Integrate between LIMS, SDMS, DQMS, and other systems.
  • Faster FDA submissions
  • Fully compliant systems with date integrity
  • Real-time quality insights within life sciences workflows
  • Well-serving APIs for integration within and outside of enterprise

Data Engineering

We help in engineering data from molecule to market within life sciences lifecycle and across integrated segments.

  • Data-driven R&D transformation
  • Robust data ingestion process throughout life sciences value chain
  • Data lake for drug discovery, clinical trial design, drug manufacturing and drug safety
  • Effective data management and data governance for regulatory compliance
  • Cloud-based data warehousing to support robust drug commercialization and drug distribution

Big Data

We help Life Sciences organizations analyze massive amounts of data from drug components, genes, proteins, etc.

  • Clinical trial results analysis and comparing with historical genomics data
  • Genomics Sequencing Analysis
  • Pharmaceutical Trial Analysis
  • Disease Risk Analysis
  • Drug Safety Analysis
  • Business research analysis for business development

Data Science

We help life sciences organizations accelerate drug discovery and drug development.

  • Model training to identify optimal features for medical diagnosis in clinic trials
  • Cutting-edge predictive models to support precision medicine studies
  • Models to help cross reference research on cancer drugs
  • Predictive algorithms to estimate side effects in post-trial
  • Estimate Bio and Pharma logistics for effective supply chain

Business Intelligence

We enable life sciences companies to access business intelligence and data visualization of pre-clinical, clinical and post-clinical research.

  • Faster and more informed clinical decisions
  • Benchmark drug safety measures
  • Segmentation and trend analysis of physicians, patients and drug sales
  • Insights to streamline product’s regulatory approval and accelerate clinical development
  • Insights to reduce operation costs including R&D expenses

Machine Learning

We help in leveraging machine learning for accelerated and improved R&D, drug development, clinical trials and supply chain.

  • Clinical trial recruitment – identify ideal candidates for clinical trials
  • Predictive modelling for drug toxicity
  • Machine Learning based trial design and drug development. Example: ADC (antibody-drug conjugates) biomaker signatures.
  • Predicting pharmacological properties of drugs and drug repurposing
  • Manufacturing optimization – production efficiency, statistical analysis, risk assessment and quality management

Deep Learning

We help in leveraging deep learning that encompasses deep neural networks to achieve breakthroughs in life sciences.

  • Large scale analysis of genes and drugs data to identify key gene for drug resistance and ADC drug payloads.
  • Analyzing biological big data with multi-layer machine learning aglorithms
  • Disease identification, disease tracking and precision modeling of patients
  • Comparative drug safety analysis in Pharmacovigilance
  • Informed clinical decision making with regulatory actions for compliance

NLP

We help in harnessing the power of NLP to extract findings from life sciences research documents and other text data.

  • Life sciences and pharma knowledge graphs
  • Adverse drug event (ADE) detection and reporting
  • Studying Adverse drug reactions (ADRs)
  • Explore drug labelling data for regulatory and safety affairs
  • Extract findings from drug and clinical research documents
  • Social listening to aid drug safety research
  • NLP text mining to build models to identify novel drug targets, drug compounds and competitor analysis.

Computer Vision

We help in leveraging computer vision algorithms to automate image and video analysis to improve end-to-end drug lifecycle.

  • Smart drug manufacturing with automated AI-powered inspections
  • Predictive maintenance of equipment in laboratories, factories, etc.
  • Smart life sciences and pharma supply chain monitoring
  • Identify small changes in cells during cancer drug research
  • Molecular modeling to reshape the drug development pipeline
  • Computer vision powered drug design helps in regulatory compliance assistance for new molecules

Chatbots

We help in deploying AI-powered assistants trained in life sciences and pharma to aid researchers, regulatory team and management in day-to-day activities.

  • Identifying relationships between entities in biotechnology, pharma and pharmacovigilance data
  • Collecting the latest news on drug trials, drug approvals, etc.
  • Accelerate pre-clinical report analysis
  • Analyze safety signals in pharmacovigilance
  • Customized AI-powered assistants for specific roles such as regulatory review, comparative analysis, conflict analysis, etc.

We help in adopting intelligent automation to leverage flexibility and speed in lab work, research, and drug development.

  • Automated ADE detection with pre-trained NLP models and pipelines
  • Automated regulator operations and corporate operations
  • Automated clinical trial management from data entry to trial reports generation
  • Automated inventory management from shipment tracking to notifying drug expiry

We help in leveraging real-time data generated by IoT for drug discovery, manufacturing and commercialization.

  • Real-time monitoring manufacturing quality and equipment for streamlined performance
  • Forecast demand for supply chain continuity
  • Better supply chain management using smart sensors for warehousing and routing of drugs
  • Real-time data insights on drug effectiveness, drug safety and regulatory compliance

We help in adopting blockchain streamline and optimize digitized critical life sciences business operations on a decentralized network.

  • End-to-end drug traceability prevents drug counterfeit
  • Fraud prevention in clinical trials
  • Robust IP protection with research data uploaded onto blockchain
  • Preventing drug shortages with untampered records for supply chain monitoring. Especially, cold chain monitoring in biopharma.
  • Reverse logistics for expired drug disposal

5G networks for faster and accurate clinical trials data transfer for decentralized clinical trials.

5G will boost Internet of Medical Things (IoMT)

5G reduces the times to process lab results from laboratories

Edge computing reduces latency and cost on data management, increases up-time, enhances data privacy across functions in life sciences.

We offer a comprehensive design expertise to help Life Sciences to build innovative products:

  • Next-gen Clinical trial solutions design
  • Multi-disciplinary approach to life sciences product design
  • Value design engineering across biotechnology, biopharma, optronics, etc.
  • Full-fledge prototypes before production

We help Life Sciences organizations to embed design thinking into their various software:

  • Evidence based UI/UX designs
  • Clinical & laboratories operations data visualization designs
  • Intuitive content experiences with research scientists as users first approach

We help the whole value chain of Life Science in developing systems with having greater agility and interoperability:

  • Clinical trial management and clinical data analysis systems
  • Laboratory information management systems (LIMS)
  • Scientific data management systems (SDMS)
  • Drug safety information management systems
  • Workflow management systems
  • Digital quality management systems (DQMS)

We help life sciences organizations in pioneering new discoveries with power of cloud:

  • Data collection through cloud for easy regulatory clearance
  • Centralized document management for streamline research
  • Enterprise level collaboration and use of advanced instruments
  • Seamless data integration from regulators, distributors, etc.
  • Cloud-based, digitized supply chain management

 

With next-gen tech stack, we help life sciences organizations deliver lifesaving products faster to the market.

  • Integrate between LIMS, SDMS, DQMS, and other systems.
  • Faster FDA submissions
  • Fully compliant systems with date integrity
  • Real-time quality insights within life sciences workflows
  • Well-serving APIs for integration within and outside of enterprise

Data Engineering

We help in engineering data from molecule to market within life sciences lifecycle and across integrated segments.

  • Data-driven R&D transformation
  • Robust data ingestion process throughout life sciences value chain
  • Data lake for drug discovery, clinical trial design, drug manufacturing and drug safety
  • Effective data management and data governance for regulatory compliance
  • Cloud-based data warehousing to support robust drug commercialization and drug distribution

Big Data

We help Life Sciences organizations analyze massive amounts of data from drug components, genes, proteins, etc.

  • Clinical trial results analysis and comparing with historical genomics data
  • Genomics Sequencing Analysis
  • Pharmaceutical Trial Analysis
  • Disease Risk Analysis
  • Drug Safety Analysis
  • Business research analysis for business development

Data Science

We help life sciences organizations accelerate drug discovery and drug development.

  • Model training to identify optimal features for medical diagnosis in clinic trials
  • Cutting-edge predictive models to support precision medicine studies
  • Models to help cross reference research on cancer drugs
  • Predictive algorithms to estimate side effects in post-trial
  • Estimate Bio and Pharma logistics for effective supply chain

Business Intelligence

We enable life sciences companies to access business intelligence and data visualization of pre-clinical, clinical and post-clinical research.

  • Faster and more informed clinical decisions
  • Benchmark drug safety measures
  • Segmentation and trend analysis of physicians, patients and drug sales
  • Insights to streamline product’s regulatory approval and accelerate clinical development
  • Insights to reduce operation costs including R&D expenses

Machine Learning

We help in leveraging machine learning for accelerated and improved R&D, drug development, clinical trials and supply chain.

  • Clinical trial recruitment – identify ideal candidates for clinical trials
  • Predictive modelling for drug toxicity
  • Machine Learning based trial design and drug development. Example: ADC (antibody-drug conjugates) biomaker signatures.
  • Predicting pharmacological properties of drugs and drug repurposing
  • Manufacturing optimization – production efficiency, statistical analysis, risk assessment and quality management

Deep Learning

We help in leveraging deep learning that encompasses deep neural networks to achieve breakthroughs in life sciences.

  • Large scale analysis of genes and drugs data to identify key gene for drug resistance and ADC drug payloads.
  • Analyzing biological big data with multi-layer machine learning aglorithms
  • Disease identification, disease tracking and precision modeling of patients
  • Comparative drug safety analysis in Pharmacovigilance
  • Informed clinical decision making with regulatory actions for compliance

NLP

We help in harnessing the power of NLP to extract findings from life sciences research documents and other text data.

  • Life sciences and pharma knowledge graphs
  • Adverse drug event (ADE) detection and reporting
  • Studying Adverse drug reactions (ADRs)
  • Explore drug labelling data for regulatory and safety affairs
  • Extract findings from drug and clinical research documents
  • Social listening to aid drug safety research
  • NLP text mining to build models to identify novel drug targets, drug compounds and competitor analysis.

Computer Vision

We help in leveraging computer vision algorithms to automate image and video analysis to improve end-to-end drug lifecycle.

  • Smart drug manufacturing with automated AI-powered inspections
  • Predictive maintenance of equipment in laboratories, factories, etc.
  • Smart life sciences and pharma supply chain monitoring
  • Identify small changes in cells during cancer drug research
  • Molecular modeling to reshape the drug development pipeline
  • Computer vision powered drug design helps in regulatory compliance assistance for new molecules

Chatbots

We help in deploying AI-powered assistants trained in life sciences and pharma to aid researchers, regulatory team and management in day-to-day activities.

  • Identifying relationships between entities in biotechnology, pharma and pharmacovigilance data
  • Collecting the latest news on drug trials, drug approvals, etc.
  • Accelerate pre-clinical report analysis
  • Analyze safety signals in pharmacovigilance
  • Customized AI-powered assistants for specific roles such as regulatory review, comparative analysis, conflict analysis, etc.

We help in adopting intelligent automation to leverage flexibility and speed in lab work, research, and drug development.

  • Automated ADE detection with pre-trained NLP models and pipelines
  • Automated regulator operations and corporate operations
  • Automated clinical trial management from data entry to trial reports generation
  • Automated inventory management from shipment tracking to notifying drug expiry

We help in leveraging real-time data generated by IoT for drug discovery, manufacturing and commercialization.

  • Real-time monitoring manufacturing quality and equipment for streamlined performance
  • Forecast demand for supply chain continuity
  • Better supply chain management using smart sensors for warehousing and routing of drugs
  • Real-time data insights on drug effectiveness, drug safety and regulatory compliance

We help in adopting blockchain streamline and optimize digitized critical life sciences business operations on a decentralized network.

  • End-to-end drug traceability prevents drug counterfeit
  • Fraud prevention in clinical trials
  • Robust IP protection with research data uploaded onto blockchain
  • Preventing drug shortages with untampered records for supply chain monitoring. Especially, cold chain monitoring in biopharma.
  • Reverse logistics for expired drug disposal

5G networks for faster and accurate clinical trials data transfer for decentralized clinical trials.

5G will boost Internet of Medical Things (IoMT)

5G reduces the times to process lab results from laboratories

Edge computing reduces latency and cost on data management, increases up-time, enhances data privacy across functions in life sciences.

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