We believe in our ideas, belief brings consistency in thoughts, planning, communication and actions

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Global Clinical portfolio on Track with timely Risk Mitigation using Clinical Operations Data Repository

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Clinical data management system and statistical computing environment

a-leap-towards-clinical-cloud-platform (1)

A leap towards clinical cloud platform

metadata-driven-process

Gaining accelerated access to data and reports through metadata-driven process from EDC to reporting

Implementation of clinical data repository in a small biotech – investment that guarantees the return

Integrating-data-repositories

Integrating data repositories for CRFs specific to your trial management processes to define data in a clinical lifecycle

Web

Drug Development 2.0

clinicalWhite Paper-01

Clinical Data Ecosystem: Ace up the sleeve

Accelerated-access-to-clinical-data

Accelerated access to clinical data and reports through Metadata-driven process from EDC to reporting

adaptive-decision-making

Adaptive decision making via real time harmonization of people, process & platform

Clinical Trails’ Renaissance: Real-time Harmonization of Composite Clinical Trials

Integrated Clinical Development Platform

A one-stop-solution for all of biopharmaceutical industry’s needs including data integration, transformation, aggregation, quality management, enrichment, analytics and reporting.

Clinical Data Repository

A single, scalable, and integrated solution that is implantable in one project that is a one stop solution for data, metadata, reporting and analytics.

Metadata Repository

MDR’s ability to efficiently manage instream Enterprise level E2E processes and audit trails from a metadata perspective and interface with MaxisIT’s integrated platform products as well as third-party products

Data Integration & Standardization Solution

completely metadata-driven, drag-n-drop data integration, transformation, and standardization solution, which offers huge reusability and drives automation with required collaboration, control, and scalability

Analytics & Reporting Solution

One solution supporting multiple analytics needs ranging from monitoring, descriptive, exploratory, trending, predictive and adaptive – all in one integrated platform.

Statistical Computing Environment

Assured Credibility of results (per Good Statistical Practice) via: reproducible, transparent and validated analysis; and a collaborative environment

Data Sciences Workbench

Ubiquitous analytical sandbox environment designed for “Data Scientists” enabling them with the desired flexibility for conducting Exploratory, Predictive and Prescriptive Analytics specifically for Data Sciences purposes.

Risk-Based Monitoring

RBM solution has the ability to function as the single point of contact for understanding, monitoring, and mitigating risks, by employing out-of-the-box integrated RBM workflows.

Data Services

Data Services model reduces manual processing thereby increasing the quality of data with reduced overall cost. Further, it allows standardized and centralized environment for end-to-end data management needs, ensuring the credibility of clinical data.

Analytics & Reporting Services

It is productive on the Integrated Platform for Clinical Development and Data Sciences environment, where they can leverage the workflows and increase the level of automation.

MaxisCloud™ Services

Incorporates high availability features including automated failover of instances, fully redundant host, network, storage hardware, and enterprise class Storage Area Networks to increase performance and reliability.

Software Implementation & Support Services

Single and multiple study based usage which provides managed services, support services and professional services.

Out of the Box Solution as a Service Experience

OBSAASE is built-on validated environment as a configurable platform to inherit the validity to newly created artifacts and is made available via high performance, and highly available computing architecture infused by on-demand scalability.

New Metadata Role for Life Sciences & Healthcare

An increasing desire for integration across verticals and patient-centric business processes means that metadata automation and collaboration matters more than ever. The historical definition of metadata is “data about data”, or “metadata is structured information that describes, explains, locates, or otherwise makes it easier to retrieve, use, or manage an information resource”.

Data Sciences – The New Analytics Paradigm

Access to data and key information for the purpose of Analytics has been a constant in the Pharmaceutical / Life Sciences / Health Care industries, and this has been true for a great deal of time.

Ensure Successful Outcomes to the Digital Revolution in Pharma

Many drug candidates and ongoing research studies into their efficacy received serious setbacks when COVID-19 resulted in the total closure of many trial study sites. There’s no saying when these studies will resume and bring deserving drug candidates to the market, to benefit a number of patients who need them, even today. This disruption to […]

Traditional vs. Remote Approach to Clinical Trial Monitoring

As the world was brought to an abrupt halt, the importance of adopting digital technologies has become apparent in all spheres of life, especially so for industries. Will the healthcare and pharmaceutical industry is quickly adopt digital technologies, , in these turbulent times, to fulfill their duty of saving lives and to attain their business […]

Can Technology bring Clinical Trials back on Track during COVID-19?

According to the statistics posted on Worldometer, the world has 803,451 active cases, with 39,044 deaths. This makes COVID_19 preparedness of the highest priority now, turning all other activities non-urgent. This pandemic is taxing the healthcare system and its capabilities, in most countries of the world. The havoc being wrought upon the world by COVID-19 […]

Clinical Trial Oversight in Parallel with COVID -19

The world has unwillingly come to a grinding halt, unsure of where to turn, with the impact of the pandemic COVID-19. Even as we submit to social distancing and lockdown requirements based on our geographic location, we are confident that ‘this too shall pass’ and we will resume our lives, ready to pick up where […]

Supporting Clinical Trials against COVID-19 with the CTOS

The world today is caught in a real predicament, living through an apocalyptic scenario, in a daze of disbelief – if not outright denial. This is no fictional account from a Robin Cook bestseller, there isn’t a heroic protagonist stepping up to contain Covid-19. Although we aren’t questioning our chances of survival yet, most aspects […]

More manpower = less development time? Not necessarily.

Hiring more manpower is not the answer to getting your clinical trials’ timelines back on track. If anything can help, that would be adoption of technology and more specifically, AI. The new way to cut the timelines of clinical trials short is to leverage artificial intelligence to drive the processes. Manage data to manage your […]

Let the Data do the Talking

What would you expect from a platform which offers to manage your clinical trials? Would you expect timely access to as authoritative, standardized and aggregated clinical trial operations data as well as patient data from site, study to portfolio level? Would you need efficient trial oversight via remote monitoring, statistically assessed controls, data quality management, […]

Everything you need to know about AI in Clinical Trials – Part 3

As discussed in Part 1 and Part 2 of AI in Clinical Trials, to process a large and continuously flowing stream of data, the pharma industry will need to employ an equally swift platform to ingest, standardize and manage the data, i.e. a holistic clinical data management platform. With the help of AI, MaxisIT’s Clinical […]

Everything you need to know about AI in Clinical Trials – Part 2

In Part-1 we discussed the problem statement and the focus areas for clinical development. We also concluded that quick access to relevant information decides the efficiency of a clinical trial. Let us now see how AI can help. An end-to-end clinical data management platform powered by artificial intelligence is the right choice for streamlining, overseeing […]

Everything you need to know about AI in Clinical Trials – Part 1

According to visionary leader Steve Jobs, if one defines the problem correctly, that person almost has the solution. And here we are discussing AI as the bellwether solution to every business/operational challenge in this world. Throw in a few AI-related words and the conversation suddenly sounds futuristic and efficient. Sure, AI is already impacting us […]

Self Service Analytics Platforms in Clinical Trials – Part 3

In Part 1 and Part 2, we discussed the self-service analytics platform and its various components. In this part we will look into the important things to consider before implementing a self-service analytics platform. The historical way of representing clinical data includes spreadsheet driven models and custom SQL queries which not only increased development time […]

Self Service Analytics Platforms in Clinical Trials – Part 2

In Part 1 we introduced self-service analytics and discussed what an ideal self-service analytics platform should accomplish. In this part, we will be discussing the various components of a modern technology platform that enables self-service analytics. Data ingestion – In a clinical trial setting, both structured and unstructured data is available from an ever-expanding range […]

Self Service Analytics Platforms in Clinical Trials – Part 1

The pharmaceuticals and lifesciences industry is undergoing transformation at an unprecedented scale mainly due to the regulatory, diminishing margins, growing amount of data and push for AI. One way to keep up with this pace of change is to create a robust analytics infrastructure that will help sponsors organizations to share information more efficiently and […]

The clinical trial metrics to keep an eye out for

As clinical studies increase in complexity in a myriad of ways, a key question often asked is, “Is our ability to create complexity increasing faster than our ability to understand complexity?” This is an exciting time to be involved in the reporting of data and metrics on the performance of a clinical study. However, it […]

Effective RBM through centralized monitoring and analytic tools

Increasing clinical development costs for drugs has been a concern for industry over the years and multidirectional efforts have been made to lower these costs through more efficient study management. Since monitoring accounts for a substantial proportion of the total study costs, major focus is towards lowering the monitoring costs through the analysis of risks […]

Covering the bases for effective Risk Based Monitoring

Post FDA’s final guidance on Risk Based Monitoring, Industry is transitioning from routine visits to clinical sites and 100% Source Data Verification to risk-based approaches to monitoring, focusing more on critical data elements by practicing Centralized Monitoring; relying more on technological advancements thus reducing trial cost and time significantly. The industry needs an out-of-the-box end […]

Using R for cross-study analysis

Clinical research is experiencing a revolution with a huge range of connected devices growing in popularity, with wearable and implantable devices across healthcare, fitness tracking and diet. Pharmaceutical companies sponsoring trials are incorporating these devices into ever more elaborate clinical trials, generating ever larger datasets, while sifting through social media streams and their own big […]

Changing landscape: Need for concept-based Metadata Repository (MDR) from protocol to data submission

The role of Master Metadata Management (MDM) MDM is a technology-enabled discipline in which business and IT work together to ensure the uniformity, accuracy, stewardship, semantic consistency and accountability of the enterprise’s official, shared master data assets. The idea of Master Data focuses on providing unobstructed access to a consistent representation of shared information. How […]

Leveraging Big Data in Clinical Trials

Industry wide Clinical Trial collaborative efforts offers significant improvement over siloed individual databases in providing superior Patient Outcomes. The efforts however were still limited to Rare Disease categories and Data Sources resulting in limited Clinical Analyses and Insight. A Clinical Data Repository utilizing Big Data will enable Pharmaceutical Cos to utilize new Analytic techniques and […]

The key to innovation in clinical studies

Clinical study designs are increasingly complex. A growing number of studies are using adaptive designs and require decisions during the conduct of the study. At the same time, the amount of data, the variety of data types and the time pressure for decision making is growing. During study conduct, scientists are under high time pressure […]

The importance of a centralized monitoring risk-based SDV approach

SDV is a very expensive process due to the time required to go through all the data at the various investigator sites. However, if we can target the patients and specify items the CRAs should look at when they visit a site, then the CRAs can spend more time looking at the important data but […]

What happens when legacy data meets CDISC Standards

CDISC standards have become an integral part of the life science industry; nevertheless, we will have to continue to deal with data in different legacy formats for some time in the future. While the use of purely CDISC-formatted data from the very beginning of a submission project is unproblematic, combining data in legacy format with […]

Data Preparation on Critical Path for Clinical Data Intelligence

Clinical organizations are under increasing pressure to execute clinical trials faster with higher quality. Subject data originates from multiple sources; CRFs collect data on patient visits, implantable devices deliver data via wireless technology. All this data needs to be integrated, cleaned and transformed from raw data to analysis datasets. This data management across multiple sources […]

Challenges to achieving quality metadata and how to overcome them.

Metadata enables exchange, review, analysis, automation and reporting of clinical data. Metadata is crucial for clinical research and standardization makes it powerful. Adherence of metadata to CDISC SDTM has become the norm, since FDA has chosen SDTM as the standard specification for submitting tabulation data for clinical trials. Today, many sponsors expect metadata to be […]

Are sponsors SEND ready?

CDISC defines SEND as an implementation of the SDTM standard for nonclinical studies. SEND specifies a way to collect and present nonclinical data in a consistent format. SEND is one of the required standards for data submission to FDA. SEND = Standard for the Exchange of Nonclinical Data. Sponsors are currently focused on processes and […]

Connecting the dots across patient journey in clinical trials using patient data repository

Industry and regulatory agencies continue to struggle implementing CDISC for both the study workflow and in support of the submission review process. Several factors contribute to these ongoing challenges including limitations within the CDISC standards themselves and the inability to represent complex relationships across clinical information in limited tools such as Excel. In our personal […]

CTOS vs CTMS, Which One Should Sponsors Choose for Effective Trial Oversight?

As the coordinator or manager of a clinical trial, you will have one simple goal: You would want your clinical trial to be successful. After all, it is your responsibility. However, to guarantee success, you need to be able to manage the project efficiently. It is of prime importance that, at any time during the […]

De-mystifying data management with automation through metadata

Things seem to be set in motion in the clinical industry when programmers ready to perform the analysis get their code-happy hands on the study data – however, once the CROs drop the data off how does it actually make the journey to the statistical programmer’s desktop? This is a critical process, but too often […]

Approaches to establishing data standards between sponsors and CROs

Small to medium size pharma companies have low adoption rates when it comes to implementing CDISC standards. Is this due to lack of awareness or understanding? How does a company that is new to standards see the wood through the trees in the new regulatory environment? Let us explore a number of approaches in how […]

A Traditional CTMS is No More the Answer to Your Clinical Trial Management Needs

Cloud-based systems eliminate huge investments into IT infrastructure with pay-as-you-go features, helping to reduce timelines, enabling the hosting of clinical trial-related data in the cloud with secured systems which meet strict regulatory and compliance guidelines, making the transfer of real time data for analysis and track studies easy. This has made a Clinical Trials Management […]

IN TIME ACTION WITH ON TIME DATA

Clinical trials that function on a global magnitude have clinical sites and patients across multiple geographies. The very nature of clinical trials brings opportunities as well as some challenges, wherein the data strewn across the globe adds more complexities to this. Amid these convoluted multiplicities, the element of BYOD, wearable technology, and mHealth applications may […]

The Superhero of Clinical Analytics & Reporting – Statistical Computational Environment

With all due respect to the herculean task undertook by the Human Genome Project which costed over 3 billion dollars and spanned over fifteen years, can be undone by parsing back the human genome in 26 hours. Though I was not involved in this project directly, it is an inspiration to a healthcare IT entrepreneur […]

A Singular Statistical Computing Framework Answers Clinical Data Diversity & More

With the complexity involved in regulatory and exploratory reporting for clinical trials, adding another element of SCE might seem overwhelming to the clinical development team particularly the biometrics team, management and investors. I, would however, contest that it can enable to reduce data to reporting cycle time and related costs; further improve the turnaround time […]

Data savvy drug development needs a Good Statistical Computing Environment (SCE)

Diverse data sources, heterogeneous data formats, the multitude of drug outputs and there is always more, within a drug development process. A highly agile and adaptable environment supported by cohesive data management and reporting processes can only accommodate and respond to the perpetuating mutations and metamorphosis in the process. Who can save the day to […]

Data, a rising mindset and methodology for drug development

I have been discovering more and more headlines reporting about genome-wide dissection of genetics, high-throughput technologies, genetic modifications and other biomedical breakthroughs. All lead to one common catalyst — a data intensive drug discovery model used by the success team. But, such a model only thrives in the presence of a sound statistical computational environment. […]

The key to faster clinical development – Identifying the potential indicators of change.

In order to avoid constrained growth model, a R&D focused organization needs to empower its business stakeholders with the cross-functional insight and portfolio-level information management strategy. Prospective solution should allow necessary roll-down and roll-up flexibilities in identifying potential indicators of change (e.g. risk and/or opportunities) and its impacts, while taking decisions with confidence. To mobilize […]

A Perfect Match – When finding the right solution provider is as important as the solution itself

The global clinical data analytics market will be worth $13.8 billion by 2023 according to a ResearchAndMarkets report. It identifies the growing popularity of EMR’s as the key driver of this growth. However the clinical development industry is still grappling with problem of disintegrated and non-standardized critical trial processes which is further handicapped by its […]

Exigency of the Industry – Integrated Clinical Development

There has been a collective realization throughout the industry that the key data management processes must show efficiency, continuous compliance, scalability, sustainability and measurable productivity gains that, over time, will transform the research and development processes used to develop new drugs. Industry leaders are addressing this problem by delivering solutions that can address various needs […]

Current Gaps in Clinical Data Management

When it comes to data management, there are a lot of data gaps that requires filling. Below are the areas of data management where the industry is facing problems. If any of this sounds familiar, you might need help! Data Capturing & Aggregation: The prevalence of ‘data heterogeneity’ in clinical trials is what makes data […]

Clinical Data Ecosystem – It’s evolving faster than ever

Since the first few citations of registered and structured clinical data in the 1940s, the methods of capturing clinical data, use and application of clinical data, global inclusions, and role of payers, users and regulators have evolved. At present, Clinical Data universe comprises of the siloed internal and external data sources within clinical development processes, […]

Rising above the data silos

How an Integrated Clinical Development Platform Helped a Client Tear Down Clinical Data Silos and Improved Decision-Making. How an Integrated Clinical Development Platform Helped a Client Tear Down Clinical Data Silos and Improved Decision-Making. The Challenge – Riddled with mélange of data and challenges in standardization which hamstrung their decision-making capabilities, our client decided to […]

Wearables in Clinical Trials – Implications for you

The demand for wearables and sensors in clinical trials is on the rise. Pharma companies are increasingly challenged with both rising costs and the need to find novel ways to differentiate the drugs they are developing. One such way is by accessing the clinical data collected on remote medical devices. By leveraging remote medical devices, […]

Saving time and cost through metadata driven reporting process

Clinical teams are often stuck in a vicious cycle of static report requests, slowing clinical data review and database lockdown. The main struggle is to unify and analyze data across domains. If data is not uniform, it restricts access to complete clinical information which will affect the decision making on safety and efficacy. It is […]

Cloud based technologies and the future of patient care in an integrated health & life sciences ecosystem

A closer look at most path-breaking enterprise cloud technologies, which have come about in the recent past, reveals that they are addressing either efficiency issues (time, cost or both), or a need which has been unaddressed or are solving for a latent need. Participants in the clinical trial industry have not been early adopters of […]

The 50th Annual Meeting of the DIA 2014

Celebrate the Past and Invent the Future with MaxisIT® at the DIA 50th Annual Meeting, June 15-19 2014 in San Diego, CA! Hosted this year at the San Diego Convention Center, the DIA Annual Meeting celebrates its 50th anniversary, as a community of life science professionals across all disciplines gather to discuss, share and network with the common goal of […]

Integrated Data Management – A Centralized Approach!

For quite some time CROs have delivered services to sponsors by hosting their clinical data, obviating the immediate need for a sponsor to build their own clinical database. This arrangement relieves the sponsor from cost and regulatory risk of establishing their own new clinical database, but can markedly compromise the sponsors’ ability to respond to […]

Case Studies
Thumbnail

Global Clinical portfolio on Track with timely Risk Mitigation using Clinical Operations Data Repository

thumbnail

Clinical data management system and statistical computing environment

a-leap-towards-clinical-cloud-platform (1)

A leap towards clinical cloud platform

metadata-driven-process

Gaining accelerated access to data and reports through metadata-driven process from EDC to reporting

Implementation of clinical data repository in a small biotech – investment that guarantees the return

Integrating-data-repositories

Integrating data repositories for CRFs specific to your trial management processes to define data in a clinical lifecycle

Whitepapers
Web

Drug Development 2.0

clinicalWhite Paper-01

Clinical Data Ecosystem: Ace up the sleeve

Accelerated-access-to-clinical-data

Accelerated access to clinical data and reports through Metadata-driven process from EDC to reporting

adaptive-decision-making

Adaptive decision making via real time harmonization of people, process & platform

Clinical Trails’ Renaissance: Real-time Harmonization of Composite Clinical Trials

Solution Brief

Integrated Clinical Development Platform

A one-stop-solution for all of biopharmaceutical industry’s needs including data integration, transformation, aggregation, quality management, enrichment, analytics and reporting.

Clinical Data Repository

A single, scalable, and integrated solution that is implantable in one project that is a one stop solution for data, metadata, reporting and analytics.

Metadata Repository

MDR’s ability to efficiently manage instream Enterprise level E2E processes and audit trails from a metadata perspective and interface with MaxisIT’s integrated platform products as well as third-party products

Data Integration & Standardization Solution

completely metadata-driven, drag-n-drop data integration, transformation, and standardization solution, which offers huge reusability and drives automation with required collaboration, control, and scalability

Analytics & Reporting Solution

One solution supporting multiple analytics needs ranging from monitoring, descriptive, exploratory, trending, predictive and adaptive – all in one integrated platform.

Statistical Computing Environment

Assured Credibility of results (per Good Statistical Practice) via: reproducible, transparent and validated analysis; and a collaborative environment

Data Sciences Workbench

Ubiquitous analytical sandbox environment designed for “Data Scientists” enabling them with the desired flexibility for conducting Exploratory, Predictive and Prescriptive Analytics specifically for Data Sciences purposes.

Risk-Based Monitoring

RBM solution has the ability to function as the single point of contact for understanding, monitoring, and mitigating risks, by employing out-of-the-box integrated RBM workflows.

Services Brief

Data Services

Data Services model reduces manual processing thereby increasing the quality of data with reduced overall cost. Further, it allows standardized and centralized environment for end-to-end data management needs, ensuring the credibility of clinical data.

Analytics & Reporting Services

It is productive on the Integrated Platform for Clinical Development and Data Sciences environment, where they can leverage the workflows and increase the level of automation.

MaxisCloud™ Services

Incorporates high availability features including automated failover of instances, fully redundant host, network, storage hardware, and enterprise class Storage Area Networks to increase performance and reliability.

Software Implementation & Support Services

Single and multiple study based usage which provides managed services, support services and professional services.

Out of the Box Solution as a Service Experience

OBSAASE is built-on validated environment as a configurable platform to inherit the validity to newly created artifacts and is made available via high performance, and highly available computing architecture infused by on-demand scalability.

Webinars

New Metadata Role for Life Sciences & Healthcare

An increasing desire for integration across verticals and patient-centric business processes means that metadata automation and collaboration matters more than ever. The historical definition of metadata is “data about data”, or “metadata is structured information that describes, explains, locates, or otherwise makes it easier to retrieve, use, or manage an information resource”.

Data Sciences – The New Analytics Paradigm

Access to data and key information for the purpose of Analytics has been a constant in the Pharmaceutical / Life Sciences / Health Care industries, and this has been true for a great deal of time.

Blog

Ensure Successful Outcomes to the Digital Revolution in Pharma

Many drug candidates and ongoing research studies into their efficacy received serious setbacks when COVID-19 resulted in the total closure of many trial study sites. There’s no saying when these studies will resume and bring deserving drug candidates to the market, to benefit a number of patients who need them, even today. This disruption to […]

Traditional vs. Remote Approach to Clinical Trial Monitoring

As the world was brought to an abrupt halt, the importance of adopting digital technologies has become apparent in all spheres of life, especially so for industries. Will the healthcare and pharmaceutical industry is quickly adopt digital technologies, , in these turbulent times, to fulfill their duty of saving lives and to attain their business […]

Can Technology bring Clinical Trials back on Track during COVID-19?

According to the statistics posted on Worldometer, the world has 803,451 active cases, with 39,044 deaths. This makes COVID_19 preparedness of the highest priority now, turning all other activities non-urgent. This pandemic is taxing the healthcare system and its capabilities, in most countries of the world. The havoc being wrought upon the world by COVID-19 […]

Clinical Trial Oversight in Parallel with COVID -19

The world has unwillingly come to a grinding halt, unsure of where to turn, with the impact of the pandemic COVID-19. Even as we submit to social distancing and lockdown requirements based on our geographic location, we are confident that ‘this too shall pass’ and we will resume our lives, ready to pick up where […]

Supporting Clinical Trials against COVID-19 with the CTOS

The world today is caught in a real predicament, living through an apocalyptic scenario, in a daze of disbelief – if not outright denial. This is no fictional account from a Robin Cook bestseller, there isn’t a heroic protagonist stepping up to contain Covid-19. Although we aren’t questioning our chances of survival yet, most aspects […]

More manpower = less development time? Not necessarily.

Hiring more manpower is not the answer to getting your clinical trials’ timelines back on track. If anything can help, that would be adoption of technology and more specifically, AI. The new way to cut the timelines of clinical trials short is to leverage artificial intelligence to drive the processes. Manage data to manage your […]

Let the Data do the Talking

What would you expect from a platform which offers to manage your clinical trials? Would you expect timely access to as authoritative, standardized and aggregated clinical trial operations data as well as patient data from site, study to portfolio level? Would you need efficient trial oversight via remote monitoring, statistically assessed controls, data quality management, […]

Everything you need to know about AI in Clinical Trials – Part 3

As discussed in Part 1 and Part 2 of AI in Clinical Trials, to process a large and continuously flowing stream of data, the pharma industry will need to employ an equally swift platform to ingest, standardize and manage the data, i.e. a holistic clinical data management platform. With the help of AI, MaxisIT’s Clinical […]

Everything you need to know about AI in Clinical Trials – Part 2

In Part-1 we discussed the problem statement and the focus areas for clinical development. We also concluded that quick access to relevant information decides the efficiency of a clinical trial. Let us now see how AI can help. An end-to-end clinical data management platform powered by artificial intelligence is the right choice for streamlining, overseeing […]

Everything you need to know about AI in Clinical Trials – Part 1

According to visionary leader Steve Jobs, if one defines the problem correctly, that person almost has the solution. And here we are discussing AI as the bellwether solution to every business/operational challenge in this world. Throw in a few AI-related words and the conversation suddenly sounds futuristic and efficient. Sure, AI is already impacting us […]

Self Service Analytics Platforms in Clinical Trials – Part 3

In Part 1 and Part 2, we discussed the self-service analytics platform and its various components. In this part we will look into the important things to consider before implementing a self-service analytics platform. The historical way of representing clinical data includes spreadsheet driven models and custom SQL queries which not only increased development time […]

Self Service Analytics Platforms in Clinical Trials – Part 2

In Part 1 we introduced self-service analytics and discussed what an ideal self-service analytics platform should accomplish. In this part, we will be discussing the various components of a modern technology platform that enables self-service analytics. Data ingestion – In a clinical trial setting, both structured and unstructured data is available from an ever-expanding range […]

Self Service Analytics Platforms in Clinical Trials – Part 1

The pharmaceuticals and lifesciences industry is undergoing transformation at an unprecedented scale mainly due to the regulatory, diminishing margins, growing amount of data and push for AI. One way to keep up with this pace of change is to create a robust analytics infrastructure that will help sponsors organizations to share information more efficiently and […]

The clinical trial metrics to keep an eye out for

As clinical studies increase in complexity in a myriad of ways, a key question often asked is, “Is our ability to create complexity increasing faster than our ability to understand complexity?” This is an exciting time to be involved in the reporting of data and metrics on the performance of a clinical study. However, it […]

Effective RBM through centralized monitoring and analytic tools

Increasing clinical development costs for drugs has been a concern for industry over the years and multidirectional efforts have been made to lower these costs through more efficient study management. Since monitoring accounts for a substantial proportion of the total study costs, major focus is towards lowering the monitoring costs through the analysis of risks […]

Covering the bases for effective Risk Based Monitoring

Post FDA’s final guidance on Risk Based Monitoring, Industry is transitioning from routine visits to clinical sites and 100% Source Data Verification to risk-based approaches to monitoring, focusing more on critical data elements by practicing Centralized Monitoring; relying more on technological advancements thus reducing trial cost and time significantly. The industry needs an out-of-the-box end […]

Using R for cross-study analysis

Clinical research is experiencing a revolution with a huge range of connected devices growing in popularity, with wearable and implantable devices across healthcare, fitness tracking and diet. Pharmaceutical companies sponsoring trials are incorporating these devices into ever more elaborate clinical trials, generating ever larger datasets, while sifting through social media streams and their own big […]

Changing landscape: Need for concept-based Metadata Repository (MDR) from protocol to data submission

The role of Master Metadata Management (MDM) MDM is a technology-enabled discipline in which business and IT work together to ensure the uniformity, accuracy, stewardship, semantic consistency and accountability of the enterprise’s official, shared master data assets. The idea of Master Data focuses on providing unobstructed access to a consistent representation of shared information. How […]

Leveraging Big Data in Clinical Trials

Industry wide Clinical Trial collaborative efforts offers significant improvement over siloed individual databases in providing superior Patient Outcomes. The efforts however were still limited to Rare Disease categories and Data Sources resulting in limited Clinical Analyses and Insight. A Clinical Data Repository utilizing Big Data will enable Pharmaceutical Cos to utilize new Analytic techniques and […]

The key to innovation in clinical studies

Clinical study designs are increasingly complex. A growing number of studies are using adaptive designs and require decisions during the conduct of the study. At the same time, the amount of data, the variety of data types and the time pressure for decision making is growing. During study conduct, scientists are under high time pressure […]

The importance of a centralized monitoring risk-based SDV approach

SDV is a very expensive process due to the time required to go through all the data at the various investigator sites. However, if we can target the patients and specify items the CRAs should look at when they visit a site, then the CRAs can spend more time looking at the important data but […]

What happens when legacy data meets CDISC Standards

CDISC standards have become an integral part of the life science industry; nevertheless, we will have to continue to deal with data in different legacy formats for some time in the future. While the use of purely CDISC-formatted data from the very beginning of a submission project is unproblematic, combining data in legacy format with […]

Data Preparation on Critical Path for Clinical Data Intelligence

Clinical organizations are under increasing pressure to execute clinical trials faster with higher quality. Subject data originates from multiple sources; CRFs collect data on patient visits, implantable devices deliver data via wireless technology. All this data needs to be integrated, cleaned and transformed from raw data to analysis datasets. This data management across multiple sources […]

Challenges to achieving quality metadata and how to overcome them.

Metadata enables exchange, review, analysis, automation and reporting of clinical data. Metadata is crucial for clinical research and standardization makes it powerful. Adherence of metadata to CDISC SDTM has become the norm, since FDA has chosen SDTM as the standard specification for submitting tabulation data for clinical trials. Today, many sponsors expect metadata to be […]

Are sponsors SEND ready?

CDISC defines SEND as an implementation of the SDTM standard for nonclinical studies. SEND specifies a way to collect and present nonclinical data in a consistent format. SEND is one of the required standards for data submission to FDA. SEND = Standard for the Exchange of Nonclinical Data. Sponsors are currently focused on processes and […]

Connecting the dots across patient journey in clinical trials using patient data repository

Industry and regulatory agencies continue to struggle implementing CDISC for both the study workflow and in support of the submission review process. Several factors contribute to these ongoing challenges including limitations within the CDISC standards themselves and the inability to represent complex relationships across clinical information in limited tools such as Excel. In our personal […]

CTOS vs CTMS, Which One Should Sponsors Choose for Effective Trial Oversight?

As the coordinator or manager of a clinical trial, you will have one simple goal: You would want your clinical trial to be successful. After all, it is your responsibility. However, to guarantee success, you need to be able to manage the project efficiently. It is of prime importance that, at any time during the […]

De-mystifying data management with automation through metadata

Things seem to be set in motion in the clinical industry when programmers ready to perform the analysis get their code-happy hands on the study data – however, once the CROs drop the data off how does it actually make the journey to the statistical programmer’s desktop? This is a critical process, but too often […]

Approaches to establishing data standards between sponsors and CROs

Small to medium size pharma companies have low adoption rates when it comes to implementing CDISC standards. Is this due to lack of awareness or understanding? How does a company that is new to standards see the wood through the trees in the new regulatory environment? Let us explore a number of approaches in how […]

A Traditional CTMS is No More the Answer to Your Clinical Trial Management Needs

Cloud-based systems eliminate huge investments into IT infrastructure with pay-as-you-go features, helping to reduce timelines, enabling the hosting of clinical trial-related data in the cloud with secured systems which meet strict regulatory and compliance guidelines, making the transfer of real time data for analysis and track studies easy. This has made a Clinical Trials Management […]

IN TIME ACTION WITH ON TIME DATA

Clinical trials that function on a global magnitude have clinical sites and patients across multiple geographies. The very nature of clinical trials brings opportunities as well as some challenges, wherein the data strewn across the globe adds more complexities to this. Amid these convoluted multiplicities, the element of BYOD, wearable technology, and mHealth applications may […]

The Superhero of Clinical Analytics & Reporting – Statistical Computational Environment

With all due respect to the herculean task undertook by the Human Genome Project which costed over 3 billion dollars and spanned over fifteen years, can be undone by parsing back the human genome in 26 hours. Though I was not involved in this project directly, it is an inspiration to a healthcare IT entrepreneur […]

A Singular Statistical Computing Framework Answers Clinical Data Diversity & More

With the complexity involved in regulatory and exploratory reporting for clinical trials, adding another element of SCE might seem overwhelming to the clinical development team particularly the biometrics team, management and investors. I, would however, contest that it can enable to reduce data to reporting cycle time and related costs; further improve the turnaround time […]

Data savvy drug development needs a Good Statistical Computing Environment (SCE)

Diverse data sources, heterogeneous data formats, the multitude of drug outputs and there is always more, within a drug development process. A highly agile and adaptable environment supported by cohesive data management and reporting processes can only accommodate and respond to the perpetuating mutations and metamorphosis in the process. Who can save the day to […]

Data, a rising mindset and methodology for drug development

I have been discovering more and more headlines reporting about genome-wide dissection of genetics, high-throughput technologies, genetic modifications and other biomedical breakthroughs. All lead to one common catalyst — a data intensive drug discovery model used by the success team. But, such a model only thrives in the presence of a sound statistical computational environment. […]

The key to faster clinical development – Identifying the potential indicators of change.

In order to avoid constrained growth model, a R&D focused organization needs to empower its business stakeholders with the cross-functional insight and portfolio-level information management strategy. Prospective solution should allow necessary roll-down and roll-up flexibilities in identifying potential indicators of change (e.g. risk and/or opportunities) and its impacts, while taking decisions with confidence. To mobilize […]

A Perfect Match – When finding the right solution provider is as important as the solution itself

The global clinical data analytics market will be worth $13.8 billion by 2023 according to a ResearchAndMarkets report. It identifies the growing popularity of EMR’s as the key driver of this growth. However the clinical development industry is still grappling with problem of disintegrated and non-standardized critical trial processes which is further handicapped by its […]

Exigency of the Industry – Integrated Clinical Development

There has been a collective realization throughout the industry that the key data management processes must show efficiency, continuous compliance, scalability, sustainability and measurable productivity gains that, over time, will transform the research and development processes used to develop new drugs. Industry leaders are addressing this problem by delivering solutions that can address various needs […]

Current Gaps in Clinical Data Management

When it comes to data management, there are a lot of data gaps that requires filling. Below are the areas of data management where the industry is facing problems. If any of this sounds familiar, you might need help! Data Capturing & Aggregation: The prevalence of ‘data heterogeneity’ in clinical trials is what makes data […]

Clinical Data Ecosystem – It’s evolving faster than ever

Since the first few citations of registered and structured clinical data in the 1940s, the methods of capturing clinical data, use and application of clinical data, global inclusions, and role of payers, users and regulators have evolved. At present, Clinical Data universe comprises of the siloed internal and external data sources within clinical development processes, […]

Rising above the data silos

How an Integrated Clinical Development Platform Helped a Client Tear Down Clinical Data Silos and Improved Decision-Making. How an Integrated Clinical Development Platform Helped a Client Tear Down Clinical Data Silos and Improved Decision-Making. The Challenge – Riddled with mélange of data and challenges in standardization which hamstrung their decision-making capabilities, our client decided to […]

Wearables in Clinical Trials – Implications for you

The demand for wearables and sensors in clinical trials is on the rise. Pharma companies are increasingly challenged with both rising costs and the need to find novel ways to differentiate the drugs they are developing. One such way is by accessing the clinical data collected on remote medical devices. By leveraging remote medical devices, […]

Saving time and cost through metadata driven reporting process

Clinical teams are often stuck in a vicious cycle of static report requests, slowing clinical data review and database lockdown. The main struggle is to unify and analyze data across domains. If data is not uniform, it restricts access to complete clinical information which will affect the decision making on safety and efficacy. It is […]

Cloud based technologies and the future of patient care in an integrated health & life sciences ecosystem

A closer look at most path-breaking enterprise cloud technologies, which have come about in the recent past, reveals that they are addressing either efficiency issues (time, cost or both), or a need which has been unaddressed or are solving for a latent need. Participants in the clinical trial industry have not been early adopters of […]

The 50th Annual Meeting of the DIA 2014

Celebrate the Past and Invent the Future with MaxisIT® at the DIA 50th Annual Meeting, June 15-19 2014 in San Diego, CA! Hosted this year at the San Diego Convention Center, the DIA Annual Meeting celebrates its 50th anniversary, as a community of life science professionals across all disciplines gather to discuss, share and network with the common goal of […]

Integrated Data Management – A Centralized Approach!

For quite some time CROs have delivered services to sponsors by hosting their clinical data, obviating the immediate need for a sponsor to build their own clinical database. This arrangement relieves the sponsor from cost and regulatory risk of establishing their own new clinical database, but can markedly compromise the sponsors’ ability to respond to […]

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