Case Studies
Modus - Immunoglycan for Sepsis
Modus aims to save countless lives using an immunoglycan, Sevuparin, that thins the blood to prevent blood clots without the risk of unwanted bleeding.
Modus aims to save countless lives using an immunoglycan, Sevuparin, that thins the blood to prevent blood clots without the risk of unwanted bleeding.
Sites Analyzed
Indications
174
174
Studies Analyzed
Studies Analyzed
7,010
7,010
Psyrin - Serious mental illness
Psyrin detects serious mental illnesses through AI-powered voice technology. SMIs affect over 145 million people worldwide, reducing expected life expectancy by 15-20 years.
Psyrin detects serious mental illnesses through AI-powered voice technology. SMIs affect over 145 million people worldwide, reducing expected life expectancy by 15-20 years.
Patient Cohorts
Indications
12
150%
Studies Analyzed
Studies Analyzed
4,809
1,790
Calmsie - Children's mental health
Analysis of patient cohorts, study landscape and enrollment data for children's mental health in the US and Europe.
Analysis of patient cohorts, study landscape and enrollment data for children's mental health in the US and Europe.
Indications
Indications
5
8
Studies Analyzed
Studies Analyzed
631
1,790
Pear Bio - Cancer therapeutics
Evaluating the clinical trial landscape for cancer drug discovery, analysing historical clinical studies and patient cohort data across breast, kidney, liver, brain, lung, colorectal, ovarian, gastric and pancreatic cancer in the US and Europe.
Evaluating the clinical trial landscape for cancer drug discovery, analysing historical clinical studies and patient cohort data across breast, kidney, liver, brain, lung, colorectal, ovarian, gastric and pancreatic cancer in the US and Europe.
Indications
Indications
8
8
Studies Analyzed
Studies Analyzed
1,790
1,790
Kheiron Medical - Breast cancer
Assessing breast cancer across 12 countries for a medical technology used for early screening of breast cancer.
Assessing breast cancer across 12 countries for a medical technology used for early screening of breast cancer.
Coming Soon
Coming Soon
Coming Soon
Countries
Countries
12
12
Studies Analyzed
Studies Analyzed
1,115
1,115
Li Ka Shing Institute of Health Sciences
Scoping the potential of clinical development across indications and countries including Hong Kong, China and the UK.
Scoping the potential of clinical development across indications and countries including Hong Kong, China and the UK.
Coming Soon
Coming Soon
Coming Soon
Indications
Indications
21
21
Studies Analyzed
Studies Analyzed
9,500
9,500
Input study parameters,
output analytics and actions
01
Patient Access
Compare Patient Access by Region. Decide on optimal site locations with patient demographic, study and site analytics
Landscape Analysis
Assess historical studies by randomization rate. Understand the drivers of studies with high RAND rates and incorporate them into your own.
02
Site Selection
Analyze sites by performance, capacity, competition and specificity. Decide which sites are relevant based on past studies and current studies that could be competing
03
Model Enrollment
Produce time estimates based off of historical data. Model enrollment scenarios with varying numbers of sites and patients in different geographies.
04
01
Patient Access
Compare Patient Access by Region. Decide on optimal site locations with patient demographic, study and site analytics
Landscape Analysis
Assess historical studies by randomization rate. Understand the drivers of studies with high RAND rates and incorporate them into your own.
02
Site Selection
Analyze sites by performance, capacity, competition and specificity. Decide which sites are relevant based on past studies and current studies that could be competing
03
Model Enrollment
Produce time estimates based off of historical data. Model enrollment scenarios with varying numbers of sites and patients in different geographies.
04
01
Patient Access
Compare Patient Access by Region. Decide on optimal site locations with patient demographic, study and site analytics
Landscape Analysis
Assess historical studies by randomization rate. Understand the drivers of studies with high RAND rates and incorporate them into your own.
02
Site Selection
Analyze sites by performance, capacity, competition and specificity. Decide which sites are relevant based on past studies and current studies that could be competing
03
Model Enrollment
Produce time estimates based off of historical data. Model enrollment scenarios with varying numbers of sites and patients in different geographies.
04
01
Patient Access
Compare Patient Access by Region. Decide on optimal site locations with patient demographic, study and site analytics
Landscape Analysis
Assess historical studies by randomization rate. Understand the drivers of studies with high RAND rates and incorporate them into your own.
02
Site Selection
Analyze sites by performance, capacity, competition and specificity. Decide which sites are relevant based on past studies and current studies that could be competing
03
Model Enrollment
Produce time estimates based off of historical data. Model enrollment scenarios with varying numbers of sites and patients in different geographies.
04
Input study parameters, output analytics and actions
01
Patient Access
Compare Patient Access by Region. Decide on optimal site locations with patient demographic, study and site analytics
Site Selection
Analyze sites by performance, capacity, competition and specificity. Decide which sites are relevant based on past studies and current studies that could be competing
03
Landscape Analysis
Assess historical studies by randomization rate. Understand the drivers of studies with high RAND rates and incorporate them into your own.
02
Model Enrollment
Produce time estimates based off of historical data. Model enrollment scenarios with varying numbers of sites and patients in different geographies.
04
Input study parameters, output analytics and actions
01
Patient Access
Compare Patient Access by Region. Decide on optimal site locations with patient demographic, study and site analytics
Site Selection
Analyze sites by performance, capacity, competition and specificity. Decide which sites are relevant based on past studies and current studies that could be competing
03
Landscape Analysis
Assess historical studies by randomization rate. Understand the drivers of studies with high RAND rates and incorporate them into your own.
02
Model Enrollment
Produce time estimates based off of historical data. Model enrollment scenarios with varying numbers of sites and patients in different geographies.
04
Turn ideas into medicine
Turn ideas into medicine
Turn ideas into medicine
