SlideShare a Scribd company logo
Investors
Pitch Deck
April 2022
About Us 3
The Opportunity 12
Our Digital Solutions 18
A-round & Projected Growth 28
Appendix (with selected case
studies)
35
ABOUT US
3
OUR MISSION
4
Longenesis: Unlocking a
healthier future by
modernizing medical data
Our mission is to help
modernize the
approach to human
health.
We firmly believe the
medical system of the
future is a collaborative
one.
A future where vital
and valuable medical
data is put to work to
find cures and
treatments while
remaining firmly within
the patient’s control.
A future where patients
can not only contribute
to medical
breakthroughs but also
experience
breakthrough, highly
personalized care for
themselves.
WHAT WE DO
5
Longenesis: Bridging
healthcare and life sciences
We provide solutions that make it easier for medical
data to be collected, analyzed, and utilized for better
care.
We bring an end-to-end, intuitive toolkit for Data
Discovery and Patient-Centric Engagement, while
being Privacy - and Ethics-by-Design at heart.
WHY US – 1/2
6
Ready to go, modular
solution covering the
whole life value chain
From data discovery to patient
engagement, our “plug and
play” solution is ready to be
deployed anywhere,
everywhere. (average
deployment time in less than a
month)
Collaborative, bespoke
approach to meet our
clients needs
With our flexible approach, we
work together with all the
involved stakeholders to meet
their needs and deploy the
most efficient and effective
solutions
Track record of
delivering at scale
Live national projects Latvia, EU
and UAE. Solutions ready to be
deployed in any country and on
any infrastructure. Already
covered more than 10
therapeutic areas and
onboarded more than 30
healthcare institutions
Exceptional adherence
and user experience
We adopt a user-centric
approach, while maintaining
compliance and prioritising
patient needs. Our latest
Engage projects have a growth
rate of >2 survey filled per day
Powered by Blockchain
Built to the highest security
standards, while providing clear
proof of patient consent for
data sharing and study
participation
WHY US – 2/2
7
Backed by sector
leaders in innovation
Such as AI drug discovery
company Insilico Medicine and
emerging technologies unicorn
The Bitfury Group
Wide team expertise
Team with multi-year global
experience in life sciences,
healthcare and technology.
Proud member of EIT Health, a
network of best-in-class health
innovators backed by the EU
Global network of
partners
Wide network of leading
researchers and clinical experts
as well as technology partners
to efficiently refine, validate and
implement our digital solutions
Awarded and valued in
the healthcare and
technology sector
Featured as a top startup to
watch by EU Startups, 50
Founders Battle. Proud finalists
for the Fair Healthdata
Challenge, Techhill, Medtech
Innovators
OUR SUCCESSFUL PROJECTS
8
2
• Government
Deployments
4+
• Big Pharma
Companies
10+
• Academic
Partners
Worldwide
250,000+
• Patients
Empowered
Worldwide
10+
• Disease
Domains
c.50%
• Reduction in
clinical trials
recruiting time
OUR RECENT ACHIEVEMENTS
9
featured in:
Finalist, 2019
Headstart COVID
winner
OUR TEAM
10
OUR ADVISORY BOARD
11
Alex Zhavoronkov, PhD – CEO and Co-founder of Insilico Medicine
Miro Venturi, PhD – Senior Vice President of Foundation Medicine
Dennis Bronnikov, MBA – Former VP of Roche, VP of Berkeley Lights
Leesa Soulodre, MBA – general partner of R3i Ventures
THE OPPORTUNITY
12
MAIN CHALLENGES WE ARE ADDRESSING
13
• Data is siloed and
unstructured
• Data organization is
time consuming,
taking months to
years
TECHNOLOGY
• Privacy risks from 3rd
party data access
• Compliant consent
curation
REGULATORY
• Patients are hard to
engage
• Patient engagement
expectations are not
met
LACK OF
PATIENT
ENGAGEMENT
Result - difficult to identify and engage patients
across multiple institutions.
9 out of 10 clinical sites
are overlooked in the
selection process
86%
Of trials are delayed
Clinical Trials Issues Example:
OUR SOLUTIONS
14
Two pillar approach:
Longenesis safely unlocks a healthier
future for humans.
We provide solutions that make it
easier for medical data to be collected,
analyzed, and utilized for better care…
…in one intuitive toolkit
TWO PILLAR APPROACH
15
Streamlines data sharing for clinical studies, bringing together healthcare and
life sciences organizations
Digital ecosystem platform that makes
data sharing for clinical studies easier.
Curator empowers clinical institutions,
researchers and patient organizations, to find
anonymized patient data for their studies,
overcoming the lengthy, ineffective and insecure
traditional identification process.
All data remains localized to its owners,
meaning sensitive medical information is
never shared with third-party servers or
stored in centralized databases
TWO PILLAR APPROACH
16
Engages patients through user-friendly education, surveys, simplified and
secured patient consent, while generating outcome based real world data
Digital platform which improves patient
management in clinical studies and
post-study activities with easy-to-use
survey creation tools, onboarding flows,
secured and compliant consent
management.
Enriches the standard of care and generates
value adding insights, leveraging real word
data analysis and support options.
Gives patients complete control over
their data, helping them feel
empowered to participate based on their
comfort level.
VALUE CREATION OPPORTUNITY FOR PHARMA
17
Earlier market launch
due to faster data
collection, study
completion(s) and
RWE insights
Reduced R&D costs
due to accelerated
participant recruitment
and increased
adherence with
engaging app
Additional market value
with improved patient
reach, additional digital
features and better
outcome based insights
C
O
S
T
R
E
V
E
N
U
E
M
A
R
K
E
T
L
A
U
N
C
H
T I M E
Drug Life-Cycle w/o Longenesis
C
O
M
P
E
T
I
T
O
R
/
G
E
N
E
R
I
C
E
N
T
R
Y
Drug Life-Cycle w/ Longenesis
Greater & sustained market
share
due to differentiated
offering and
enhanced engagement
1 2 3 4
1
2
3
4
OUR DIGITAL SOLUTIONS
18
OUR ECOSYSTEM
19
DATA
DISCOVERY
ENGAGEMENT
DATA PUBLISHERS
(Biobanks, Hospitals,
Biotech, Research
Groups)
PARTNERS/SPONSORS
(Academic Institutions, Pharma,
CRO, Research Groups, AI
Companies, Governmental
Organizations)
Biomedical fully
anonymized metadata
Surveys, Risk stratification, Analysis,
Complications and Side-effect
monitoring, Consent Management
• Platform providing real-time,
borderless, biomedical data or/and
patient identification, ensuring data
privacy and security and following
bioethics compliance
• Centralized meta-data curation
and discovery ecosystem with
decentralized data storage
• Robust solution for proactive full
patient engagement cycle into
prospective studies and multi-
channel data gathering and
personalized feedback, driving Real
World Data (RWD) collection
empowering smarter decisions
The value added by our solutions
DATA DISCOVERY WITH CURATOR
1 YEAR OF WORK IN DAYS. ENABLING REAL-TIME DATA DISCOVERY, WHILE DATA STAYS LOCAL
20
Identify patients in existing
healthcare provider
network
Discover new clinical sites fit
for research
Send direct data or patient
access requests straight to
clinical sites
1
2
3
WHY METADATA
STATISTICAL OVERVIEW OF SITE’S PATIENT POPULATION WITH NO PHI OR DATA INGESTION
21
Curator operates with anonymized
statistical patient information without
PHI, uploaded directly by sites
themselves
• Health data always stays local
• No PHI is accessed
• No EMR integrations or data
ingestion is performed
WHY CURATOR
22
•Non-invasive
•No privacy risks
•Uses anonymized
metadata
Patient-
centered
•Takes 1-2 days to
onboard a site
•Allows exports from any
EMR
Easy to use
•Extensive library of 30+
clinical sites in EU and
MENA available
Wide-
reaching
•Explores the patient
population at a new
clinical site in just hours
•Rapidly identify datasets
and engage potential
study participants
Fast and
effective
OVERVIEW OF ENGAGE FUNCTIONALITIES
23
VALUE ADDED
CLINICAL
TRIALS
MARKETED
DRUGS
DEPLOYMENT EXAMPLES
End-to-end dynamic
consent management
Full cycle of consent registration and management, as
well as biomedical/clinical data processing
Ready to be integrated into already existing interfaces, or
to be used as stand-alone, white-labelled solution.
Real-time instrument for consent review and audit,
ensuring privacy and protection
End-to-end consent management
for prospective study onboarding
for National Population Genome
program in the Middle East,
Real World Data
(RWD) collection
empowering smarter
decisions
Dynamic participant-centric interface for RWD collection
and personalized reporting, questionnaires and risk
assessments
Wider engagement possibilities, higher retention rates,
simplified process, as well as faster insights from patient-
reported data.
COVID-19 population studies,
personalized breast cancer-
related risk assessment, other
disease-specific QoL
Type 1 diabetes research study
with leading med-tech and patient
organizations to launch a new
patient-centric engagement
mechanism
PATIENT-CENTRIC PATIENT ENGAGEMENT
PATIENT-CENTRICITY BY DESIGN
24
Creates rapid participant /patient
engagement experience at the clinical
site level and/or for marketed drugs
Allows dynamic consent management,
pre-screening, questionnaires, risk
assessments and RWD generation
Enriches Curator with anonymized
metadata
DYNAMIC E-CONSENT MANAGEMENT
EMPOWERING PATIENTS WITH ETHICS BY DESIGN
25
A real-time instrument for consent
audit for clinical researchers
Empowering patients with a right to
decide where, how and why the data
will be used
API ready to be integrated in any
interface
WHY ENGAGE
26
• Run patient-centric onboarding
and RWD generation from
participants in existing and
newly discovered clinical sites,
as well as for marketed drugs
• Non-invasive
Patient-
centered
• Experience intuitive ease of use
Easy to use
• Meet evolving patient
expectations for proactive
engagement
Better proactive
engagement
• Rapidly identify datasets and
engage potential study
participants, significantly
reducing time and costs of
clinical trials
• Generates outcome-based
insights for marketed drugs,
ultimately increasing drugs
revenues and market share
Fast and
effective
REGULATORY STATUS
27
Engagement Module
• Adhering to HIPAA/GDPR/PIPA
framework
• Regional cloud deployments
• Working towards ISO
Data Discovery Module
• No access to PHI or raw/processed
data
• Regional cloud deployments
A-ROUND & PROJECTED GROWTH
28
OUR JOURNEY SO FAR
29
Our Funding History
2017
Q2
2021
Q2
2022
Longenesis Founded
1.2m USD Seed
Round
540k USD bridge
round
7.3m USD pre-
money valuation
Our Achievements
Both data
discovery and
engagement
products
deployed
Solutions already
scaling up in the
EU and MENA
region (100%
revenue growth
in 2021)
Ongoing
partnership
closing process
with large
customers in the
pipeline
Commercial
capacity
expansion (BD
lead &
marketing
activities) and
legal entity
setup (move
from HK to US)
in preparation
for A-round
A-ROUND FUNDING STRATEGY
30
Business
Development
• Scale up presence in the EU and MENA regions, both in pharma and healthcare
sector
• Expansion of existing pharma and governmental use cases
• Further landing of strategic technical partnerships
Product
Development
• Development of new additional features in line with received customer
feedback, such as: [ES TO INTEGRATE]
• Targeted expansion of product team to support new developments and new
potential regulatory requirements
Operations
• Expansion of business development resources to support envisioned growth
• Expansion of business support functions and systems (finance, legal,
compliance) to support growth and A-round requirements
• Additional marketing and customer success resources to enhance company
branding and marketing strategy
A-round envisioned timeline
Q3
2022
Q1
2023
Q2
2023
Completion of
required diligence
5m USD A-round
Phase 1
5m USD A-round
Phase 2
10m USD A-round
at 30m USD pre-
money valuation
OUR FINANCIAL PERFORMANCE
31
€ 110,000
€ 280,000
€ 660,000
€ 1,220,000
€ 2,500,000
€ 4,000,000
2020 2021 2022 2023 2024 2025
• >100% growth in 2021
• Group 42 Healthcare (UAE) - 140k
EUR
• Response to Covid projects with LV
and EU partners - 32k and 45k EUR
• Collaboration with research
consortium (EU) and university
hospitals on patient identification
with rare skin diseases - 105k EUR
2020-21 Results
• 100% YoY growth by converting
pilots into large paying customers
and scaling-up our international reach
• See following slide for key accounts
strategy details
Strategic Plan
Actuals
Forecast
2022-23 COMMERCIAL FOCUS
32
€ -
€ 100,000
€ 200,000
€ 300,000
€ 400,000
G42 (secured) Intel FL (trial
pending)
IROS
(agreement
pending)
Alexion (trial
pending)
Intel Neom
(agreement
pending)
Others
Our main accounts
2022 2023
• closing international
pilots and building our
user base through their
networks
2022 Focus
• converting pilots into
large paying customers
and scaling-up our
international reach
2023 Focus
CUSTOMER SUCCESS & SCALABILITY
33
Avg. deployment time (days) N. of filled surveys Avg. survey / day
35 (11 for the last two
projects)
>110
0.5 (2.5 for the last two
projects)
N. of Data Publishers
Data Publishers with
uploaded data
N. of covered
therapeutic areas
Avg. deployment
time (days)
30 >50% >10 20
Capturing customer feedback and scaling up quickly
OUR SCALABLE PARTNERSHIP BUSINESS MODEL
34
Deploy Curator and Engage in a disease-
specific clinical study for data discovery and
participant engagement
Partnership Opportunities
Use Curator with
existing network of
sponsor’s sites, use
Engage to engage
participants
Use Curator to
discover new sites
in a specific area,
use Engage to
engage participants
Build together a
use case with
Curator to bring
together sites in
scope, use Engage
to engage
participants
Our Business Model
Partnership with Pharma / CRO
Flat fixed fee
for Curator
access
SaaS tiered
pricing for
Engage access,
depending on
participant
cohort
APPENDIX AND SELECTED CASE STUDIES
35
EFFICIENT IDENTIFICATION AND MULTI-MODAL DIAGNOSTIC
SYSTEM FOR RARE SKIN DISEASES
36
Partner
Challenge
Need for a new screening system and clinical testing for
effective diagnosis of patients with undiagnosed rare skin
diseases.
Achievements
Developed a new screening system combines tools for
patient identification – Engage and Curator, followed by
multimodal dermatoscopic evaluation.
System is based on a dynamic survey module, where active
clinicians in hospitals can quickly and easily describe
patients' diagnostic criteria, disease history, and insights
from anywhere in the world
MECHANISMS OF COPING WITH PANDEMIC-INDUCED
INDIVIDUAL ECONOMIC SHOCKS
37
Partner
Challenge
Understand the impact of economic shocks and uncertainty
on long-term mental health
Achievements
Longenesis Engage digitally engages participants in the
study and provides a platform in multiple languages.
Project is carried out as a collaboration of the seven
European universities within the framework of FORTHEM-
Alliance
INDIVIDUAL APPROACH IN THE TREATMENT OF MULTIPLE
SCLEROSIS PATIENTS
38
Partner
Challenge
Provide researchers with a robust tool for medical
treatment outcome monitoring and enables the participants
to oversee their data.
Achievements
The solution ensures a smoother engagement process via
digital onboarding and follow-up communication.
TRACKING THE LONG COVID SYMPTOMS DIGITALLY
39
Partner
Challenge
Develop a survey to help identify different post-COVID
conditions based on regular parent evaluation of their
children's symptoms.
Provide an anonymise collected data overview without
compromising privacy.
Achievements
Engage enables triage of patients for whether they can
continue to recover at home or pursue an appointment with
a medical professional.
Curator enables increased proximity to vital data for
biomedical research and eliminated the need for additional
integrations or third-party data access
A MULTI-CENTRE QOL STUDY AMONG TYPE 1 DIABETICS FOR
MARKET ACCESS & CHANGES IN REIMBURSEMENT STRATEGY
40
Partner
Medtronic, Children University hospital, University of
Latvia
Challenge
Time-constrained QoL data gathering for market access
package
Achievements
120+ patients identified via Curator and engaged in the
study
Patients were motivated by dynamic consent tool and
being proactively engaged
High retention for follow-ups >80%
Delighted customer
FEDERATING LEARNING - ENABLING OF LOCAL AI MODEL
TRAINING FOR A MAJOR PHARMA CLIENT IN PEDIATRICS
41
Partner
Global Pharma + Leading Tech Company + several
pediatric hospitals
Challenge
Need to discover data for local AI model training
Need to obtain relevant patient permissions for data usage
Achievements
Data successfully discovered in multiple pediatric
“federations”
Data used for AI training with patient permissions obtained
RWD MARKET ACCESS STUDY ON THE USE OF ORAL
CONTRACEPTIVES
42
Partner EU-based Pharma with a portfolio of fertility products
Challenge
Inability to gather data among pre-screening population
Lack of proactive engagement of population
Achievements
6000+ female participants engaged in personalized risk
assessment and prospective RWD studies
Platform provides ability to validate any public health and
disease-specific hypothesis in real-time

More Related Content

What's hot

SF Big Analytics 20190612: Building highly efficient data lakes using Apache ...
SF Big Analytics 20190612: Building highly efficient data lakes using Apache ...SF Big Analytics 20190612: Building highly efficient data lakes using Apache ...
SF Big Analytics 20190612: Building highly efficient data lakes using Apache ...
Chester Chen
 
Best Practices of HA and Replication of PostgreSQL in Virtualized Environments
Best Practices of HA and Replication of PostgreSQL in Virtualized EnvironmentsBest Practices of HA and Replication of PostgreSQL in Virtualized Environments
Best Practices of HA and Replication of PostgreSQL in Virtualized Environments
Jignesh Shah
 
Serving the Real-Time Data Needs of an Airport with Kafka Streams and KSQL
Serving the Real-Time Data Needs of an Airport with Kafka Streams and KSQL Serving the Real-Time Data Needs of an Airport with Kafka Streams and KSQL
Serving the Real-Time Data Needs of an Airport with Kafka Streams and KSQL
confluent
 
Capital One Delivers Risk Insights in Real Time with Stream Processing
Capital One Delivers Risk Insights in Real Time with Stream ProcessingCapital One Delivers Risk Insights in Real Time with Stream Processing
Capital One Delivers Risk Insights in Real Time with Stream Processing
confluent
 
Top 5 Event Streaming Use Cases for 2021 with Apache Kafka
Top 5 Event Streaming Use Cases for 2021 with Apache KafkaTop 5 Event Streaming Use Cases for 2021 with Apache Kafka
Top 5 Event Streaming Use Cases for 2021 with Apache Kafka
Kai Wähner
 
Lessons in Linear Algebra at Scale with Apache Spark : Let's Make the Sparse ...
Lessons in Linear Algebra at Scale with Apache Spark : Let's Make the Sparse ...Lessons in Linear Algebra at Scale with Apache Spark : Let's Make the Sparse ...
Lessons in Linear Algebra at Scale with Apache Spark : Let's Make the Sparse ...
Databricks
 
Intro to Delta Lake
Intro to Delta LakeIntro to Delta Lake
Intro to Delta Lake
Databricks
 
[DSC Europe 22] Lakehouse architecture with Delta Lake and Databricks - Draga...
[DSC Europe 22] Lakehouse architecture with Delta Lake and Databricks - Draga...[DSC Europe 22] Lakehouse architecture with Delta Lake and Databricks - Draga...
[DSC Europe 22] Lakehouse architecture with Delta Lake and Databricks - Draga...
DataScienceConferenc1
 
Local Secondary Indexes in Apache Phoenix
Local Secondary Indexes in Apache PhoenixLocal Secondary Indexes in Apache Phoenix
Local Secondary Indexes in Apache Phoenix
Rajeshbabu Chintaguntla
 
Reshape Data Lake (as of 2020.07)
Reshape Data Lake (as of 2020.07)Reshape Data Lake (as of 2020.07)
Reshape Data Lake (as of 2020.07)
Eric Sun
 
rise-with-sap-s4hana-cloud-private-edition-and-sap-erp-pce-english-v2-2021.pdf
rise-with-sap-s4hana-cloud-private-edition-and-sap-erp-pce-english-v2-2021.pdfrise-with-sap-s4hana-cloud-private-edition-and-sap-erp-pce-english-v2-2021.pdf
rise-with-sap-s4hana-cloud-private-edition-and-sap-erp-pce-english-v2-2021.pdf
BangLuuVan
 
Introduction to Spark Streaming
Introduction to Spark StreamingIntroduction to Spark Streaming
Introduction to Spark Streaming
datamantra
 
Strongly Consistent Global Indexes for Apache Phoenix
Strongly Consistent Global Indexes for Apache PhoenixStrongly Consistent Global Indexes for Apache Phoenix
Strongly Consistent Global Indexes for Apache Phoenix
YugabyteDB
 
Iceberg: A modern table format for big data (Strata NY 2018)
Iceberg: A modern table format for big data (Strata NY 2018)Iceberg: A modern table format for big data (Strata NY 2018)
Iceberg: A modern table format for big data (Strata NY 2018)
Ryan Blue
 
Interactive real time dashboards on data streams using Kafka, Druid, and Supe...
Interactive real time dashboards on data streams using Kafka, Druid, and Supe...Interactive real time dashboards on data streams using Kafka, Druid, and Supe...
Interactive real time dashboards on data streams using Kafka, Druid, and Supe...
DataWorks Summit
 
Maxscale 소개 1.1.1
Maxscale 소개 1.1.1Maxscale 소개 1.1.1
Maxscale 소개 1.1.1
NeoClova
 
Fundamentals of Stream Processing with Apache Beam, Tyler Akidau, Frances Perry
Fundamentals of Stream Processing with Apache Beam, Tyler Akidau, Frances Perry Fundamentals of Stream Processing with Apache Beam, Tyler Akidau, Frances Perry
Fundamentals of Stream Processing with Apache Beam, Tyler Akidau, Frances Perry
confluent
 
Simplifying Real-Time Architectures for IoT with Apache Kudu
Simplifying Real-Time Architectures for IoT with Apache KuduSimplifying Real-Time Architectures for IoT with Apache Kudu
Simplifying Real-Time Architectures for IoT with Apache Kudu
Cloudera, Inc.
 
Fluentd and Kafka
Fluentd and KafkaFluentd and Kafka
Fluentd and Kafka
N Masahiro
 
How to Store and Visualize CAN Bus Telematic Data with InfluxDB Cloud and Gra...
How to Store and Visualize CAN Bus Telematic Data with InfluxDB Cloud and Gra...How to Store and Visualize CAN Bus Telematic Data with InfluxDB Cloud and Gra...
How to Store and Visualize CAN Bus Telematic Data with InfluxDB Cloud and Gra...
InfluxData
 

What's hot (20)

SF Big Analytics 20190612: Building highly efficient data lakes using Apache ...
SF Big Analytics 20190612: Building highly efficient data lakes using Apache ...SF Big Analytics 20190612: Building highly efficient data lakes using Apache ...
SF Big Analytics 20190612: Building highly efficient data lakes using Apache ...
 
Best Practices of HA and Replication of PostgreSQL in Virtualized Environments
Best Practices of HA and Replication of PostgreSQL in Virtualized EnvironmentsBest Practices of HA and Replication of PostgreSQL in Virtualized Environments
Best Practices of HA and Replication of PostgreSQL in Virtualized Environments
 
Serving the Real-Time Data Needs of an Airport with Kafka Streams and KSQL
Serving the Real-Time Data Needs of an Airport with Kafka Streams and KSQL Serving the Real-Time Data Needs of an Airport with Kafka Streams and KSQL
Serving the Real-Time Data Needs of an Airport with Kafka Streams and KSQL
 
Capital One Delivers Risk Insights in Real Time with Stream Processing
Capital One Delivers Risk Insights in Real Time with Stream ProcessingCapital One Delivers Risk Insights in Real Time with Stream Processing
Capital One Delivers Risk Insights in Real Time with Stream Processing
 
Top 5 Event Streaming Use Cases for 2021 with Apache Kafka
Top 5 Event Streaming Use Cases for 2021 with Apache KafkaTop 5 Event Streaming Use Cases for 2021 with Apache Kafka
Top 5 Event Streaming Use Cases for 2021 with Apache Kafka
 
Lessons in Linear Algebra at Scale with Apache Spark : Let's Make the Sparse ...
Lessons in Linear Algebra at Scale with Apache Spark : Let's Make the Sparse ...Lessons in Linear Algebra at Scale with Apache Spark : Let's Make the Sparse ...
Lessons in Linear Algebra at Scale with Apache Spark : Let's Make the Sparse ...
 
Intro to Delta Lake
Intro to Delta LakeIntro to Delta Lake
Intro to Delta Lake
 
[DSC Europe 22] Lakehouse architecture with Delta Lake and Databricks - Draga...
[DSC Europe 22] Lakehouse architecture with Delta Lake and Databricks - Draga...[DSC Europe 22] Lakehouse architecture with Delta Lake and Databricks - Draga...
[DSC Europe 22] Lakehouse architecture with Delta Lake and Databricks - Draga...
 
Local Secondary Indexes in Apache Phoenix
Local Secondary Indexes in Apache PhoenixLocal Secondary Indexes in Apache Phoenix
Local Secondary Indexes in Apache Phoenix
 
Reshape Data Lake (as of 2020.07)
Reshape Data Lake (as of 2020.07)Reshape Data Lake (as of 2020.07)
Reshape Data Lake (as of 2020.07)
 
rise-with-sap-s4hana-cloud-private-edition-and-sap-erp-pce-english-v2-2021.pdf
rise-with-sap-s4hana-cloud-private-edition-and-sap-erp-pce-english-v2-2021.pdfrise-with-sap-s4hana-cloud-private-edition-and-sap-erp-pce-english-v2-2021.pdf
rise-with-sap-s4hana-cloud-private-edition-and-sap-erp-pce-english-v2-2021.pdf
 
Introduction to Spark Streaming
Introduction to Spark StreamingIntroduction to Spark Streaming
Introduction to Spark Streaming
 
Strongly Consistent Global Indexes for Apache Phoenix
Strongly Consistent Global Indexes for Apache PhoenixStrongly Consistent Global Indexes for Apache Phoenix
Strongly Consistent Global Indexes for Apache Phoenix
 
Iceberg: A modern table format for big data (Strata NY 2018)
Iceberg: A modern table format for big data (Strata NY 2018)Iceberg: A modern table format for big data (Strata NY 2018)
Iceberg: A modern table format for big data (Strata NY 2018)
 
Interactive real time dashboards on data streams using Kafka, Druid, and Supe...
Interactive real time dashboards on data streams using Kafka, Druid, and Supe...Interactive real time dashboards on data streams using Kafka, Druid, and Supe...
Interactive real time dashboards on data streams using Kafka, Druid, and Supe...
 
Maxscale 소개 1.1.1
Maxscale 소개 1.1.1Maxscale 소개 1.1.1
Maxscale 소개 1.1.1
 
Fundamentals of Stream Processing with Apache Beam, Tyler Akidau, Frances Perry
Fundamentals of Stream Processing with Apache Beam, Tyler Akidau, Frances Perry Fundamentals of Stream Processing with Apache Beam, Tyler Akidau, Frances Perry
Fundamentals of Stream Processing with Apache Beam, Tyler Akidau, Frances Perry
 
Simplifying Real-Time Architectures for IoT with Apache Kudu
Simplifying Real-Time Architectures for IoT with Apache KuduSimplifying Real-Time Architectures for IoT with Apache Kudu
Simplifying Real-Time Architectures for IoT with Apache Kudu
 
Fluentd and Kafka
Fluentd and KafkaFluentd and Kafka
Fluentd and Kafka
 
How to Store and Visualize CAN Bus Telematic Data with InfluxDB Cloud and Gra...
How to Store and Visualize CAN Bus Telematic Data with InfluxDB Cloud and Gra...How to Store and Visualize CAN Bus Telematic Data with InfluxDB Cloud and Gra...
How to Store and Visualize CAN Bus Telematic Data with InfluxDB Cloud and Gra...
 

Similar to Longenesis_Investors_TechChill.pdf

M-health for cost savings and care management
M-health for cost savings and care managementM-health for cost savings and care management
M-health for cost savings and care management
Andy Arends
 
Dr Roblee
Dr RobleeDr Roblee
Dr Roblee
markacruzdds
 
Avident deck crowdfunding 3 21 18 slideshare
Avident deck crowdfunding 3 21 18 slideshareAvident deck crowdfunding 3 21 18 slideshare
Avident deck crowdfunding 3 21 18 slideshare
Maen Farha
 
Delivering real world evidence to demonstrate product safety and value
Delivering real world evidence to demonstrate product safety and valueDelivering real world evidence to demonstrate product safety and value
Delivering real world evidence to demonstrate product safety and value
Kishan Patel, MBA
 
The Role of Data Lakes in Healthcare
The Role of Data Lakes in HealthcareThe Role of Data Lakes in Healthcare
The Role of Data Lakes in Healthcare
Perficient, Inc.
 
Telehealth Remote Monitoring and Diagnostics
Telehealth Remote Monitoring and DiagnosticsTelehealth Remote Monitoring and Diagnostics
Telehealth Remote Monitoring and Diagnostics
Ammar
 
SeHF 2014 | Tackling the Tsunami: Building an mHealth Strategy
SeHF 2014 | Tackling the Tsunami: Building an mHealth StrategySeHF 2014 | Tackling the Tsunami: Building an mHealth Strategy
SeHF 2014 | Tackling the Tsunami: Building an mHealth Strategy
Swiss eHealth Forum
 
A Trust-Centric Healthcare Journey Part II | Full Presentation of PharmaLedge...
A Trust-Centric Healthcare Journey Part II | Full Presentation of PharmaLedge...A Trust-Centric Healthcare Journey Part II | Full Presentation of PharmaLedge...
A Trust-Centric Healthcare Journey Part II | Full Presentation of PharmaLedge...
PharmaLedger
 
From Edge Case to Main Case, Michelle Longmire of Medable_mHealth Israel
From Edge Case to Main Case, Michelle Longmire of Medable_mHealth IsraelFrom Edge Case to Main Case, Michelle Longmire of Medable_mHealth Israel
From Edge Case to Main Case, Michelle Longmire of Medable_mHealth Israel
Levi Shapiro
 
MediPi cost-effective_remote_patient_monitoring_using_a_raspberry_pi_single_b...
MediPi cost-effective_remote_patient_monitoring_using_a_raspberry_pi_single_b...MediPi cost-effective_remote_patient_monitoring_using_a_raspberry_pi_single_b...
MediPi cost-effective_remote_patient_monitoring_using_a_raspberry_pi_single_b...
Richard Robinson
 
Keys to Building a Successful Mobile Health Strategy
Keys to Building a Successful Mobile Health StrategyKeys to Building a Successful Mobile Health Strategy
Keys to Building a Successful Mobile Health Strategy
David Lee Scher, MD
 
GetPersonalized! : Your data, your choice, your healthbank, Healthbank
GetPersonalized! : Your data, your choice, your healthbank, HealthbankGetPersonalized! : Your data, your choice, your healthbank, Healthbank
GetPersonalized! : Your data, your choice, your healthbank, Healthbank
Sitra / Hyvinvointi
 
2016 IBM Interconnect - medical devices transformation
2016 IBM Interconnect  - medical devices transformation2016 IBM Interconnect  - medical devices transformation
2016 IBM Interconnect - medical devices transformation
Elizabeth Koumpan
 
United healthcare trends discussion by Frost & Sullivan
United healthcare trends discussion by Frost & SullivanUnited healthcare trends discussion by Frost & Sullivan
United healthcare trends discussion by Frost & Sullivan
Modupe Sarratt
 
Deborah Weinswig's Digital Health Presentation for NACDS Aug. 24, 2015
Deborah Weinswig's Digital Health Presentation for NACDS Aug. 24, 2015Deborah Weinswig's Digital Health Presentation for NACDS Aug. 24, 2015
Deborah Weinswig's Digital Health Presentation for NACDS Aug. 24, 2015
Deborah Weinswig
 
The FDA Digital Health Center of Excellence and the Advancement of Digital He...
The FDA Digital Health Center of Excellence and the Advancement of Digital He...The FDA Digital Health Center of Excellence and the Advancement of Digital He...
The FDA Digital Health Center of Excellence and the Advancement of Digital He...
Greenlight Guru
 
The IMI EHDEN project: large-scale analysis of observation data in Europe - C...
The IMI EHDEN project: large-scale analysis of observation data in Europe - C...The IMI EHDEN project: large-scale analysis of observation data in Europe - C...
The IMI EHDEN project: large-scale analysis of observation data in Europe - C...
Maxim Moinat
 
Connected Health & Me - Matic Meglic - Nov 24th 2014
Connected Health & Me - Matic Meglic - Nov 24th 2014Connected Health & Me - Matic Meglic - Nov 24th 2014
Connected Health & Me - Matic Meglic - Nov 24th 2014
ipposi
 
The application of new technologies and IT in Health: standards as infrastruc...
The application of new technologies and IT in Health: standards as infrastruc...The application of new technologies and IT in Health: standards as infrastruc...
The application of new technologies and IT in Health: standards as infrastruc...
Trillium Bridge: Reinforcing the Bridges and Scaling up EU/US Cooperation on Patient Summary
 
Real World Late Phase The right approach for the right question
Real World Late Phase The right approach for the right questionReal World Late Phase The right approach for the right question
Real World Late Phase The right approach for the right question
Satish Kumar
 

Similar to Longenesis_Investors_TechChill.pdf (20)

M-health for cost savings and care management
M-health for cost savings and care managementM-health for cost savings and care management
M-health for cost savings and care management
 
Dr Roblee
Dr RobleeDr Roblee
Dr Roblee
 
Avident deck crowdfunding 3 21 18 slideshare
Avident deck crowdfunding 3 21 18 slideshareAvident deck crowdfunding 3 21 18 slideshare
Avident deck crowdfunding 3 21 18 slideshare
 
Delivering real world evidence to demonstrate product safety and value
Delivering real world evidence to demonstrate product safety and valueDelivering real world evidence to demonstrate product safety and value
Delivering real world evidence to demonstrate product safety and value
 
The Role of Data Lakes in Healthcare
The Role of Data Lakes in HealthcareThe Role of Data Lakes in Healthcare
The Role of Data Lakes in Healthcare
 
Telehealth Remote Monitoring and Diagnostics
Telehealth Remote Monitoring and DiagnosticsTelehealth Remote Monitoring and Diagnostics
Telehealth Remote Monitoring and Diagnostics
 
SeHF 2014 | Tackling the Tsunami: Building an mHealth Strategy
SeHF 2014 | Tackling the Tsunami: Building an mHealth StrategySeHF 2014 | Tackling the Tsunami: Building an mHealth Strategy
SeHF 2014 | Tackling the Tsunami: Building an mHealth Strategy
 
A Trust-Centric Healthcare Journey Part II | Full Presentation of PharmaLedge...
A Trust-Centric Healthcare Journey Part II | Full Presentation of PharmaLedge...A Trust-Centric Healthcare Journey Part II | Full Presentation of PharmaLedge...
A Trust-Centric Healthcare Journey Part II | Full Presentation of PharmaLedge...
 
From Edge Case to Main Case, Michelle Longmire of Medable_mHealth Israel
From Edge Case to Main Case, Michelle Longmire of Medable_mHealth IsraelFrom Edge Case to Main Case, Michelle Longmire of Medable_mHealth Israel
From Edge Case to Main Case, Michelle Longmire of Medable_mHealth Israel
 
MediPi cost-effective_remote_patient_monitoring_using_a_raspberry_pi_single_b...
MediPi cost-effective_remote_patient_monitoring_using_a_raspberry_pi_single_b...MediPi cost-effective_remote_patient_monitoring_using_a_raspberry_pi_single_b...
MediPi cost-effective_remote_patient_monitoring_using_a_raspberry_pi_single_b...
 
Keys to Building a Successful Mobile Health Strategy
Keys to Building a Successful Mobile Health StrategyKeys to Building a Successful Mobile Health Strategy
Keys to Building a Successful Mobile Health Strategy
 
GetPersonalized! : Your data, your choice, your healthbank, Healthbank
GetPersonalized! : Your data, your choice, your healthbank, HealthbankGetPersonalized! : Your data, your choice, your healthbank, Healthbank
GetPersonalized! : Your data, your choice, your healthbank, Healthbank
 
2016 IBM Interconnect - medical devices transformation
2016 IBM Interconnect  - medical devices transformation2016 IBM Interconnect  - medical devices transformation
2016 IBM Interconnect - medical devices transformation
 
United healthcare trends discussion by Frost & Sullivan
United healthcare trends discussion by Frost & SullivanUnited healthcare trends discussion by Frost & Sullivan
United healthcare trends discussion by Frost & Sullivan
 
Deborah Weinswig's Digital Health Presentation for NACDS Aug. 24, 2015
Deborah Weinswig's Digital Health Presentation for NACDS Aug. 24, 2015Deborah Weinswig's Digital Health Presentation for NACDS Aug. 24, 2015
Deborah Weinswig's Digital Health Presentation for NACDS Aug. 24, 2015
 
The FDA Digital Health Center of Excellence and the Advancement of Digital He...
The FDA Digital Health Center of Excellence and the Advancement of Digital He...The FDA Digital Health Center of Excellence and the Advancement of Digital He...
The FDA Digital Health Center of Excellence and the Advancement of Digital He...
 
The IMI EHDEN project: large-scale analysis of observation data in Europe - C...
The IMI EHDEN project: large-scale analysis of observation data in Europe - C...The IMI EHDEN project: large-scale analysis of observation data in Europe - C...
The IMI EHDEN project: large-scale analysis of observation data in Europe - C...
 
Connected Health & Me - Matic Meglic - Nov 24th 2014
Connected Health & Me - Matic Meglic - Nov 24th 2014Connected Health & Me - Matic Meglic - Nov 24th 2014
Connected Health & Me - Matic Meglic - Nov 24th 2014
 
The application of new technologies and IT in Health: standards as infrastruc...
The application of new technologies and IT in Health: standards as infrastruc...The application of new technologies and IT in Health: standards as infrastruc...
The application of new technologies and IT in Health: standards as infrastruc...
 
Real World Late Phase The right approach for the right question
Real World Late Phase The right approach for the right questionReal World Late Phase The right approach for the right question
Real World Late Phase The right approach for the right question
 

Recently uploaded

Apps Break Data
Apps Break DataApps Break Data
Apps Break Data
Ivo Velitchkov
 
Monitoring and Managing Anomaly Detection on OpenShift.pdf
Monitoring and Managing Anomaly Detection on OpenShift.pdfMonitoring and Managing Anomaly Detection on OpenShift.pdf
Monitoring and Managing Anomaly Detection on OpenShift.pdf
Tosin Akinosho
 
Nordic Marketo Engage User Group_June 13_ 2024.pptx
Nordic Marketo Engage User Group_June 13_ 2024.pptxNordic Marketo Engage User Group_June 13_ 2024.pptx
Nordic Marketo Engage User Group_June 13_ 2024.pptx
MichaelKnudsen27
 
5th LF Energy Power Grid Model Meet-up Slides
5th LF Energy Power Grid Model Meet-up Slides5th LF Energy Power Grid Model Meet-up Slides
5th LF Energy Power Grid Model Meet-up Slides
DanBrown980551
 
9 CEO's who hit $100m ARR Share Their Top Growth Tactics Nathan Latka, Founde...
9 CEO's who hit $100m ARR Share Their Top Growth Tactics Nathan Latka, Founde...9 CEO's who hit $100m ARR Share Their Top Growth Tactics Nathan Latka, Founde...
9 CEO's who hit $100m ARR Share Their Top Growth Tactics Nathan Latka, Founde...
saastr
 
AppSec PNW: Android and iOS Application Security with MobSF
AppSec PNW: Android and iOS Application Security with MobSFAppSec PNW: Android and iOS Application Security with MobSF
AppSec PNW: Android and iOS Application Security with MobSF
Ajin Abraham
 
Connector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectors
Connector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectorsConnector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectors
Connector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectors
DianaGray10
 
Biomedical Knowledge Graphs for Data Scientists and Bioinformaticians
Biomedical Knowledge Graphs for Data Scientists and BioinformaticiansBiomedical Knowledge Graphs for Data Scientists and Bioinformaticians
Biomedical Knowledge Graphs for Data Scientists and Bioinformaticians
Neo4j
 
PRODUCT LISTING OPTIMIZATION PRESENTATION.pptx
PRODUCT LISTING OPTIMIZATION PRESENTATION.pptxPRODUCT LISTING OPTIMIZATION PRESENTATION.pptx
PRODUCT LISTING OPTIMIZATION PRESENTATION.pptx
christinelarrosa
 
Northern Engraving | Modern Metal Trim, Nameplates and Appliance Panels
Northern Engraving | Modern Metal Trim, Nameplates and Appliance PanelsNorthern Engraving | Modern Metal Trim, Nameplates and Appliance Panels
Northern Engraving | Modern Metal Trim, Nameplates and Appliance Panels
Northern Engraving
 
Session 1 - Intro to Robotic Process Automation.pdf
Session 1 - Intro to Robotic Process Automation.pdfSession 1 - Intro to Robotic Process Automation.pdf
Session 1 - Intro to Robotic Process Automation.pdf
UiPathCommunity
 
Dandelion Hashtable: beyond billion requests per second on a commodity server
Dandelion Hashtable: beyond billion requests per second on a commodity serverDandelion Hashtable: beyond billion requests per second on a commodity server
Dandelion Hashtable: beyond billion requests per second on a commodity server
Antonios Katsarakis
 
zkStudyClub - LatticeFold: A Lattice-based Folding Scheme and its Application...
zkStudyClub - LatticeFold: A Lattice-based Folding Scheme and its Application...zkStudyClub - LatticeFold: A Lattice-based Folding Scheme and its Application...
zkStudyClub - LatticeFold: A Lattice-based Folding Scheme and its Application...
Alex Pruden
 
“Temporal Event Neural Networks: A More Efficient Alternative to the Transfor...
“Temporal Event Neural Networks: A More Efficient Alternative to the Transfor...“Temporal Event Neural Networks: A More Efficient Alternative to the Transfor...
“Temporal Event Neural Networks: A More Efficient Alternative to the Transfor...
Edge AI and Vision Alliance
 
Crafting Excellence: A Comprehensive Guide to iOS Mobile App Development Serv...
Crafting Excellence: A Comprehensive Guide to iOS Mobile App Development Serv...Crafting Excellence: A Comprehensive Guide to iOS Mobile App Development Serv...
Crafting Excellence: A Comprehensive Guide to iOS Mobile App Development Serv...
Pitangent Analytics & Technology Solutions Pvt. Ltd
 
"$10 thousand per minute of downtime: architecture, queues, streaming and fin...
"$10 thousand per minute of downtime: architecture, queues, streaming and fin..."$10 thousand per minute of downtime: architecture, queues, streaming and fin...
"$10 thousand per minute of downtime: architecture, queues, streaming and fin...
Fwdays
 
Christine's Supplier Sourcing Presentaion.pptx
Christine's Supplier Sourcing Presentaion.pptxChristine's Supplier Sourcing Presentaion.pptx
Christine's Supplier Sourcing Presentaion.pptx
christinelarrosa
 
Main news related to the CCS TSI 2023 (2023/1695)
Main news related to the CCS TSI 2023 (2023/1695)Main news related to the CCS TSI 2023 (2023/1695)
Main news related to the CCS TSI 2023 (2023/1695)
Jakub Marek
 
"Scaling RAG Applications to serve millions of users", Kevin Goedecke
"Scaling RAG Applications to serve millions of users",  Kevin Goedecke"Scaling RAG Applications to serve millions of users",  Kevin Goedecke
"Scaling RAG Applications to serve millions of users", Kevin Goedecke
Fwdays
 
Mutation Testing for Task-Oriented Chatbots
Mutation Testing for Task-Oriented ChatbotsMutation Testing for Task-Oriented Chatbots
Mutation Testing for Task-Oriented Chatbots
Pablo Gómez Abajo
 

Recently uploaded (20)

Apps Break Data
Apps Break DataApps Break Data
Apps Break Data
 
Monitoring and Managing Anomaly Detection on OpenShift.pdf
Monitoring and Managing Anomaly Detection on OpenShift.pdfMonitoring and Managing Anomaly Detection on OpenShift.pdf
Monitoring and Managing Anomaly Detection on OpenShift.pdf
 
Nordic Marketo Engage User Group_June 13_ 2024.pptx
Nordic Marketo Engage User Group_June 13_ 2024.pptxNordic Marketo Engage User Group_June 13_ 2024.pptx
Nordic Marketo Engage User Group_June 13_ 2024.pptx
 
5th LF Energy Power Grid Model Meet-up Slides
5th LF Energy Power Grid Model Meet-up Slides5th LF Energy Power Grid Model Meet-up Slides
5th LF Energy Power Grid Model Meet-up Slides
 
9 CEO's who hit $100m ARR Share Their Top Growth Tactics Nathan Latka, Founde...
9 CEO's who hit $100m ARR Share Their Top Growth Tactics Nathan Latka, Founde...9 CEO's who hit $100m ARR Share Their Top Growth Tactics Nathan Latka, Founde...
9 CEO's who hit $100m ARR Share Their Top Growth Tactics Nathan Latka, Founde...
 
AppSec PNW: Android and iOS Application Security with MobSF
AppSec PNW: Android and iOS Application Security with MobSFAppSec PNW: Android and iOS Application Security with MobSF
AppSec PNW: Android and iOS Application Security with MobSF
 
Connector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectors
Connector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectorsConnector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectors
Connector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectors
 
Biomedical Knowledge Graphs for Data Scientists and Bioinformaticians
Biomedical Knowledge Graphs for Data Scientists and BioinformaticiansBiomedical Knowledge Graphs for Data Scientists and Bioinformaticians
Biomedical Knowledge Graphs for Data Scientists and Bioinformaticians
 
PRODUCT LISTING OPTIMIZATION PRESENTATION.pptx
PRODUCT LISTING OPTIMIZATION PRESENTATION.pptxPRODUCT LISTING OPTIMIZATION PRESENTATION.pptx
PRODUCT LISTING OPTIMIZATION PRESENTATION.pptx
 
Northern Engraving | Modern Metal Trim, Nameplates and Appliance Panels
Northern Engraving | Modern Metal Trim, Nameplates and Appliance PanelsNorthern Engraving | Modern Metal Trim, Nameplates and Appliance Panels
Northern Engraving | Modern Metal Trim, Nameplates and Appliance Panels
 
Session 1 - Intro to Robotic Process Automation.pdf
Session 1 - Intro to Robotic Process Automation.pdfSession 1 - Intro to Robotic Process Automation.pdf
Session 1 - Intro to Robotic Process Automation.pdf
 
Dandelion Hashtable: beyond billion requests per second on a commodity server
Dandelion Hashtable: beyond billion requests per second on a commodity serverDandelion Hashtable: beyond billion requests per second on a commodity server
Dandelion Hashtable: beyond billion requests per second on a commodity server
 
zkStudyClub - LatticeFold: A Lattice-based Folding Scheme and its Application...
zkStudyClub - LatticeFold: A Lattice-based Folding Scheme and its Application...zkStudyClub - LatticeFold: A Lattice-based Folding Scheme and its Application...
zkStudyClub - LatticeFold: A Lattice-based Folding Scheme and its Application...
 
“Temporal Event Neural Networks: A More Efficient Alternative to the Transfor...
“Temporal Event Neural Networks: A More Efficient Alternative to the Transfor...“Temporal Event Neural Networks: A More Efficient Alternative to the Transfor...
“Temporal Event Neural Networks: A More Efficient Alternative to the Transfor...
 
Crafting Excellence: A Comprehensive Guide to iOS Mobile App Development Serv...
Crafting Excellence: A Comprehensive Guide to iOS Mobile App Development Serv...Crafting Excellence: A Comprehensive Guide to iOS Mobile App Development Serv...
Crafting Excellence: A Comprehensive Guide to iOS Mobile App Development Serv...
 
"$10 thousand per minute of downtime: architecture, queues, streaming and fin...
"$10 thousand per minute of downtime: architecture, queues, streaming and fin..."$10 thousand per minute of downtime: architecture, queues, streaming and fin...
"$10 thousand per minute of downtime: architecture, queues, streaming and fin...
 
Christine's Supplier Sourcing Presentaion.pptx
Christine's Supplier Sourcing Presentaion.pptxChristine's Supplier Sourcing Presentaion.pptx
Christine's Supplier Sourcing Presentaion.pptx
 
Main news related to the CCS TSI 2023 (2023/1695)
Main news related to the CCS TSI 2023 (2023/1695)Main news related to the CCS TSI 2023 (2023/1695)
Main news related to the CCS TSI 2023 (2023/1695)
 
"Scaling RAG Applications to serve millions of users", Kevin Goedecke
"Scaling RAG Applications to serve millions of users",  Kevin Goedecke"Scaling RAG Applications to serve millions of users",  Kevin Goedecke
"Scaling RAG Applications to serve millions of users", Kevin Goedecke
 
Mutation Testing for Task-Oriented Chatbots
Mutation Testing for Task-Oriented ChatbotsMutation Testing for Task-Oriented Chatbots
Mutation Testing for Task-Oriented Chatbots
 

Longenesis_Investors_TechChill.pdf

  • 2. About Us 3 The Opportunity 12 Our Digital Solutions 18 A-round & Projected Growth 28 Appendix (with selected case studies) 35
  • 4. OUR MISSION 4 Longenesis: Unlocking a healthier future by modernizing medical data Our mission is to help modernize the approach to human health. We firmly believe the medical system of the future is a collaborative one. A future where vital and valuable medical data is put to work to find cures and treatments while remaining firmly within the patient’s control. A future where patients can not only contribute to medical breakthroughs but also experience breakthrough, highly personalized care for themselves.
  • 5. WHAT WE DO 5 Longenesis: Bridging healthcare and life sciences We provide solutions that make it easier for medical data to be collected, analyzed, and utilized for better care. We bring an end-to-end, intuitive toolkit for Data Discovery and Patient-Centric Engagement, while being Privacy - and Ethics-by-Design at heart.
  • 6. WHY US – 1/2 6 Ready to go, modular solution covering the whole life value chain From data discovery to patient engagement, our “plug and play” solution is ready to be deployed anywhere, everywhere. (average deployment time in less than a month) Collaborative, bespoke approach to meet our clients needs With our flexible approach, we work together with all the involved stakeholders to meet their needs and deploy the most efficient and effective solutions Track record of delivering at scale Live national projects Latvia, EU and UAE. Solutions ready to be deployed in any country and on any infrastructure. Already covered more than 10 therapeutic areas and onboarded more than 30 healthcare institutions Exceptional adherence and user experience We adopt a user-centric approach, while maintaining compliance and prioritising patient needs. Our latest Engage projects have a growth rate of >2 survey filled per day Powered by Blockchain Built to the highest security standards, while providing clear proof of patient consent for data sharing and study participation
  • 7. WHY US – 2/2 7 Backed by sector leaders in innovation Such as AI drug discovery company Insilico Medicine and emerging technologies unicorn The Bitfury Group Wide team expertise Team with multi-year global experience in life sciences, healthcare and technology. Proud member of EIT Health, a network of best-in-class health innovators backed by the EU Global network of partners Wide network of leading researchers and clinical experts as well as technology partners to efficiently refine, validate and implement our digital solutions Awarded and valued in the healthcare and technology sector Featured as a top startup to watch by EU Startups, 50 Founders Battle. Proud finalists for the Fair Healthdata Challenge, Techhill, Medtech Innovators
  • 8. OUR SUCCESSFUL PROJECTS 8 2 • Government Deployments 4+ • Big Pharma Companies 10+ • Academic Partners Worldwide 250,000+ • Patients Empowered Worldwide 10+ • Disease Domains c.50% • Reduction in clinical trials recruiting time
  • 9. OUR RECENT ACHIEVEMENTS 9 featured in: Finalist, 2019 Headstart COVID winner
  • 11. OUR ADVISORY BOARD 11 Alex Zhavoronkov, PhD – CEO and Co-founder of Insilico Medicine Miro Venturi, PhD – Senior Vice President of Foundation Medicine Dennis Bronnikov, MBA – Former VP of Roche, VP of Berkeley Lights Leesa Soulodre, MBA – general partner of R3i Ventures
  • 13. MAIN CHALLENGES WE ARE ADDRESSING 13 • Data is siloed and unstructured • Data organization is time consuming, taking months to years TECHNOLOGY • Privacy risks from 3rd party data access • Compliant consent curation REGULATORY • Patients are hard to engage • Patient engagement expectations are not met LACK OF PATIENT ENGAGEMENT Result - difficult to identify and engage patients across multiple institutions. 9 out of 10 clinical sites are overlooked in the selection process 86% Of trials are delayed Clinical Trials Issues Example:
  • 14. OUR SOLUTIONS 14 Two pillar approach: Longenesis safely unlocks a healthier future for humans. We provide solutions that make it easier for medical data to be collected, analyzed, and utilized for better care… …in one intuitive toolkit
  • 15. TWO PILLAR APPROACH 15 Streamlines data sharing for clinical studies, bringing together healthcare and life sciences organizations Digital ecosystem platform that makes data sharing for clinical studies easier. Curator empowers clinical institutions, researchers and patient organizations, to find anonymized patient data for their studies, overcoming the lengthy, ineffective and insecure traditional identification process. All data remains localized to its owners, meaning sensitive medical information is never shared with third-party servers or stored in centralized databases
  • 16. TWO PILLAR APPROACH 16 Engages patients through user-friendly education, surveys, simplified and secured patient consent, while generating outcome based real world data Digital platform which improves patient management in clinical studies and post-study activities with easy-to-use survey creation tools, onboarding flows, secured and compliant consent management. Enriches the standard of care and generates value adding insights, leveraging real word data analysis and support options. Gives patients complete control over their data, helping them feel empowered to participate based on their comfort level.
  • 17. VALUE CREATION OPPORTUNITY FOR PHARMA 17 Earlier market launch due to faster data collection, study completion(s) and RWE insights Reduced R&D costs due to accelerated participant recruitment and increased adherence with engaging app Additional market value with improved patient reach, additional digital features and better outcome based insights C O S T R E V E N U E M A R K E T L A U N C H T I M E Drug Life-Cycle w/o Longenesis C O M P E T I T O R / G E N E R I C E N T R Y Drug Life-Cycle w/ Longenesis Greater & sustained market share due to differentiated offering and enhanced engagement 1 2 3 4 1 2 3 4
  • 19. OUR ECOSYSTEM 19 DATA DISCOVERY ENGAGEMENT DATA PUBLISHERS (Biobanks, Hospitals, Biotech, Research Groups) PARTNERS/SPONSORS (Academic Institutions, Pharma, CRO, Research Groups, AI Companies, Governmental Organizations) Biomedical fully anonymized metadata Surveys, Risk stratification, Analysis, Complications and Side-effect monitoring, Consent Management • Platform providing real-time, borderless, biomedical data or/and patient identification, ensuring data privacy and security and following bioethics compliance • Centralized meta-data curation and discovery ecosystem with decentralized data storage • Robust solution for proactive full patient engagement cycle into prospective studies and multi- channel data gathering and personalized feedback, driving Real World Data (RWD) collection empowering smarter decisions The value added by our solutions
  • 20. DATA DISCOVERY WITH CURATOR 1 YEAR OF WORK IN DAYS. ENABLING REAL-TIME DATA DISCOVERY, WHILE DATA STAYS LOCAL 20 Identify patients in existing healthcare provider network Discover new clinical sites fit for research Send direct data or patient access requests straight to clinical sites 1 2 3
  • 21. WHY METADATA STATISTICAL OVERVIEW OF SITE’S PATIENT POPULATION WITH NO PHI OR DATA INGESTION 21 Curator operates with anonymized statistical patient information without PHI, uploaded directly by sites themselves • Health data always stays local • No PHI is accessed • No EMR integrations or data ingestion is performed
  • 22. WHY CURATOR 22 •Non-invasive •No privacy risks •Uses anonymized metadata Patient- centered •Takes 1-2 days to onboard a site •Allows exports from any EMR Easy to use •Extensive library of 30+ clinical sites in EU and MENA available Wide- reaching •Explores the patient population at a new clinical site in just hours •Rapidly identify datasets and engage potential study participants Fast and effective
  • 23. OVERVIEW OF ENGAGE FUNCTIONALITIES 23 VALUE ADDED CLINICAL TRIALS MARKETED DRUGS DEPLOYMENT EXAMPLES End-to-end dynamic consent management Full cycle of consent registration and management, as well as biomedical/clinical data processing Ready to be integrated into already existing interfaces, or to be used as stand-alone, white-labelled solution. Real-time instrument for consent review and audit, ensuring privacy and protection End-to-end consent management for prospective study onboarding for National Population Genome program in the Middle East, Real World Data (RWD) collection empowering smarter decisions Dynamic participant-centric interface for RWD collection and personalized reporting, questionnaires and risk assessments Wider engagement possibilities, higher retention rates, simplified process, as well as faster insights from patient- reported data. COVID-19 population studies, personalized breast cancer- related risk assessment, other disease-specific QoL Type 1 diabetes research study with leading med-tech and patient organizations to launch a new patient-centric engagement mechanism
  • 24. PATIENT-CENTRIC PATIENT ENGAGEMENT PATIENT-CENTRICITY BY DESIGN 24 Creates rapid participant /patient engagement experience at the clinical site level and/or for marketed drugs Allows dynamic consent management, pre-screening, questionnaires, risk assessments and RWD generation Enriches Curator with anonymized metadata
  • 25. DYNAMIC E-CONSENT MANAGEMENT EMPOWERING PATIENTS WITH ETHICS BY DESIGN 25 A real-time instrument for consent audit for clinical researchers Empowering patients with a right to decide where, how and why the data will be used API ready to be integrated in any interface
  • 26. WHY ENGAGE 26 • Run patient-centric onboarding and RWD generation from participants in existing and newly discovered clinical sites, as well as for marketed drugs • Non-invasive Patient- centered • Experience intuitive ease of use Easy to use • Meet evolving patient expectations for proactive engagement Better proactive engagement • Rapidly identify datasets and engage potential study participants, significantly reducing time and costs of clinical trials • Generates outcome-based insights for marketed drugs, ultimately increasing drugs revenues and market share Fast and effective
  • 27. REGULATORY STATUS 27 Engagement Module • Adhering to HIPAA/GDPR/PIPA framework • Regional cloud deployments • Working towards ISO Data Discovery Module • No access to PHI or raw/processed data • Regional cloud deployments
  • 28. A-ROUND & PROJECTED GROWTH 28
  • 29. OUR JOURNEY SO FAR 29 Our Funding History 2017 Q2 2021 Q2 2022 Longenesis Founded 1.2m USD Seed Round 540k USD bridge round 7.3m USD pre- money valuation Our Achievements Both data discovery and engagement products deployed Solutions already scaling up in the EU and MENA region (100% revenue growth in 2021) Ongoing partnership closing process with large customers in the pipeline Commercial capacity expansion (BD lead & marketing activities) and legal entity setup (move from HK to US) in preparation for A-round
  • 30. A-ROUND FUNDING STRATEGY 30 Business Development • Scale up presence in the EU and MENA regions, both in pharma and healthcare sector • Expansion of existing pharma and governmental use cases • Further landing of strategic technical partnerships Product Development • Development of new additional features in line with received customer feedback, such as: [ES TO INTEGRATE] • Targeted expansion of product team to support new developments and new potential regulatory requirements Operations • Expansion of business development resources to support envisioned growth • Expansion of business support functions and systems (finance, legal, compliance) to support growth and A-round requirements • Additional marketing and customer success resources to enhance company branding and marketing strategy A-round envisioned timeline Q3 2022 Q1 2023 Q2 2023 Completion of required diligence 5m USD A-round Phase 1 5m USD A-round Phase 2 10m USD A-round at 30m USD pre- money valuation
  • 31. OUR FINANCIAL PERFORMANCE 31 € 110,000 € 280,000 € 660,000 € 1,220,000 € 2,500,000 € 4,000,000 2020 2021 2022 2023 2024 2025 • >100% growth in 2021 • Group 42 Healthcare (UAE) - 140k EUR • Response to Covid projects with LV and EU partners - 32k and 45k EUR • Collaboration with research consortium (EU) and university hospitals on patient identification with rare skin diseases - 105k EUR 2020-21 Results • 100% YoY growth by converting pilots into large paying customers and scaling-up our international reach • See following slide for key accounts strategy details Strategic Plan Actuals Forecast
  • 32. 2022-23 COMMERCIAL FOCUS 32 € - € 100,000 € 200,000 € 300,000 € 400,000 G42 (secured) Intel FL (trial pending) IROS (agreement pending) Alexion (trial pending) Intel Neom (agreement pending) Others Our main accounts 2022 2023 • closing international pilots and building our user base through their networks 2022 Focus • converting pilots into large paying customers and scaling-up our international reach 2023 Focus
  • 33. CUSTOMER SUCCESS & SCALABILITY 33 Avg. deployment time (days) N. of filled surveys Avg. survey / day 35 (11 for the last two projects) >110 0.5 (2.5 for the last two projects) N. of Data Publishers Data Publishers with uploaded data N. of covered therapeutic areas Avg. deployment time (days) 30 >50% >10 20 Capturing customer feedback and scaling up quickly
  • 34. OUR SCALABLE PARTNERSHIP BUSINESS MODEL 34 Deploy Curator and Engage in a disease- specific clinical study for data discovery and participant engagement Partnership Opportunities Use Curator with existing network of sponsor’s sites, use Engage to engage participants Use Curator to discover new sites in a specific area, use Engage to engage participants Build together a use case with Curator to bring together sites in scope, use Engage to engage participants Our Business Model Partnership with Pharma / CRO Flat fixed fee for Curator access SaaS tiered pricing for Engage access, depending on participant cohort
  • 35. APPENDIX AND SELECTED CASE STUDIES 35
  • 36. EFFICIENT IDENTIFICATION AND MULTI-MODAL DIAGNOSTIC SYSTEM FOR RARE SKIN DISEASES 36 Partner Challenge Need for a new screening system and clinical testing for effective diagnosis of patients with undiagnosed rare skin diseases. Achievements Developed a new screening system combines tools for patient identification – Engage and Curator, followed by multimodal dermatoscopic evaluation. System is based on a dynamic survey module, where active clinicians in hospitals can quickly and easily describe patients' diagnostic criteria, disease history, and insights from anywhere in the world
  • 37. MECHANISMS OF COPING WITH PANDEMIC-INDUCED INDIVIDUAL ECONOMIC SHOCKS 37 Partner Challenge Understand the impact of economic shocks and uncertainty on long-term mental health Achievements Longenesis Engage digitally engages participants in the study and provides a platform in multiple languages. Project is carried out as a collaboration of the seven European universities within the framework of FORTHEM- Alliance
  • 38. INDIVIDUAL APPROACH IN THE TREATMENT OF MULTIPLE SCLEROSIS PATIENTS 38 Partner Challenge Provide researchers with a robust tool for medical treatment outcome monitoring and enables the participants to oversee their data. Achievements The solution ensures a smoother engagement process via digital onboarding and follow-up communication.
  • 39. TRACKING THE LONG COVID SYMPTOMS DIGITALLY 39 Partner Challenge Develop a survey to help identify different post-COVID conditions based on regular parent evaluation of their children's symptoms. Provide an anonymise collected data overview without compromising privacy. Achievements Engage enables triage of patients for whether they can continue to recover at home or pursue an appointment with a medical professional. Curator enables increased proximity to vital data for biomedical research and eliminated the need for additional integrations or third-party data access
  • 40. A MULTI-CENTRE QOL STUDY AMONG TYPE 1 DIABETICS FOR MARKET ACCESS & CHANGES IN REIMBURSEMENT STRATEGY 40 Partner Medtronic, Children University hospital, University of Latvia Challenge Time-constrained QoL data gathering for market access package Achievements 120+ patients identified via Curator and engaged in the study Patients were motivated by dynamic consent tool and being proactively engaged High retention for follow-ups >80% Delighted customer
  • 41. FEDERATING LEARNING - ENABLING OF LOCAL AI MODEL TRAINING FOR A MAJOR PHARMA CLIENT IN PEDIATRICS 41 Partner Global Pharma + Leading Tech Company + several pediatric hospitals Challenge Need to discover data for local AI model training Need to obtain relevant patient permissions for data usage Achievements Data successfully discovered in multiple pediatric “federations” Data used for AI training with patient permissions obtained
  • 42. RWD MARKET ACCESS STUDY ON THE USE OF ORAL CONTRACEPTIVES 42 Partner EU-based Pharma with a portfolio of fertility products Challenge Inability to gather data among pre-screening population Lack of proactive engagement of population Achievements 6000+ female participants engaged in personalized risk assessment and prospective RWD studies Platform provides ability to validate any public health and disease-specific hypothesis in real-time