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PRODID:www.eu-parc.eu
BEGIN:VEVENT
UID:69f3b22c44637
DTSTART;VALUE=DATE:20250609
SEQUENCE:0
TRANSP:OPAQUE
DTEND;VALUE=DATE:20250610
SUMMARY:PARC Modelers'\; Meeting – Advancing Chemical Risk Assessment
through Modeling
CLASS:PUBLIC
DESCRIPTION:The PARC Modelers' Meeting will bring together modelers and dat
a managers from multiple PARC work packages and related activities. This i
nternal meeting aims to review progress\, discuss future directions\, and
strengthen collaborations in the field of chemical risk assessment modelin
g. \;The meeting will focus on five core modeling areas: \;Physiol
ogically Based Kinetic (PBK) Models – Covering both toxicokinetic and ph
armacokinetic modeling.Quantitative Structure-Activity Relationships (QSAR
) – Exploring modern machine learning and artificial neural network appr
oaches.Artificial Intelligence (AI) in Chemical Risk Assessment (CRA) –
Examining AI applications beyond QSAR in CRA.Exposure Models – Discussin
g advancements in exposure modeling techniques.Data Management – Address
ing challenges and opportunities in data/model organization and integratio
n. \;The meeting will provide a collaborative platform for PARC modele
rs and data managers to exchange expertise\, align strategies\, and enhanc
e synergy between different work packages. This event will be instrumental
in shaping the future of modeling within PARC\, fostering interdisciplina
ry collaboration\, and driving innovation in chemical risk assessment. Par
ticipants are encouraged to contribute actively to discussions and knowled
ge-sharing sessions. \; \;
X-ALT-DESC;FMTTYPE=text/html:The PARC Modelers' Meeting will bring toge
ther modelers and data managers from multiple PARC work packages and relat
ed activities. This internal meeting aims to review progress\, dis
cuss future directions\, and strengthen collaborations in the fie
ld of chemical risk assessment modeling. \;
The meeting will focus on five core modeling areas: \;
Physiologically Based Kinetic (PBK) Models – Cove
ring both toxicokinetic and pharmacokinetic modeling.Quan
titative Structure-Activity Relationships (QSAR) – Exploring mo
dern machine learning and artificial neural network approaches.Artificial Intelligence (AI) in Chemical Risk Assessment (CRA) – Examining AI applications beyond QSAR in CRA.Expo
sure Models – Discussing advancements in exposure modeling tech
niques.Data Management – Addressing challenges
and opportunities in data/model organization and integration. \;
The meeting will provide a collaborative platform
for PARC modelers and data managers to exchange expertise\, align strateg
ies\, and enhance synergy between different work packages. This event will
be instrumental in shaping the future of modeling within PARC\, fostering
interdisciplinary collaboration\, and driving innovation in chemical risk
assessment. Participants are encouraged to contribute actively to discuss
ions and knowledge-sharing sessions.
\;
\;
X-MICROSOFT-CDO-ALLDAYEVENT:TRUE
DTSTAMP:20260430T194900Z
END:VEVENT
BEGIN:VEVENT
UID:69f3b22c446a9
DTSTART;VALUE=DATE:20250610
SEQUENCE:0
TRANSP:OPAQUE
DTEND;VALUE=DATE:20250611
SUMMARY:PARC Modelers'\; Meeting – Advancing Chemical Risk Assessment
through Modeling
CLASS:PUBLIC
DESCRIPTION:The PARC Modelers' Meeting will bring together modelers and dat
a managers from multiple PARC work packages and related activities. This i
nternal meeting aims to review progress\, discuss future directions\, and
strengthen collaborations in the field of chemical risk assessment modelin
g. \;The meeting will focus on five core modeling areas: \;Physiol
ogically Based Kinetic (PBK) Models – Covering both toxicokinetic and ph
armacokinetic modeling.Quantitative Structure-Activity Relationships (QSAR
) – Exploring modern machine learning and artificial neural network appr
oaches.Artificial Intelligence (AI) in Chemical Risk Assessment (CRA) –
Examining AI applications beyond QSAR in CRA.Exposure Models – Discussin
g advancements in exposure modeling techniques.Data Management – Address
ing challenges and opportunities in data/model organization and integratio
n. \;The meeting will provide a collaborative platform for PARC modele
rs and data managers to exchange expertise\, align strategies\, and enhanc
e synergy between different work packages. This event will be instrumental
in shaping the future of modeling within PARC\, fostering interdisciplina
ry collaboration\, and driving innovation in chemical risk assessment. Par
ticipants are encouraged to contribute actively to discussions and knowled
ge-sharing sessions. \; \;
X-ALT-DESC;FMTTYPE=text/html:The PARC Modelers' Meeting will bring toge
ther modelers and data managers from multiple PARC work packages and relat
ed activities. This internal meeting aims to review progress\, dis
cuss future directions\, and strengthen collaborations in the fie
ld of chemical risk assessment modeling. \;
The meeting will focus on five core modeling areas: \;
Physiologically Based Kinetic (PBK) Models – Cove
ring both toxicokinetic and pharmacokinetic modeling.Quan
titative Structure-Activity Relationships (QSAR) – Exploring mo
dern machine learning and artificial neural network approaches.Artificial Intelligence (AI) in Chemical Risk Assessment (CRA) – Examining AI applications beyond QSAR in CRA.Expo
sure Models – Discussing advancements in exposure modeling tech
niques.Data Management – Addressing challenges
and opportunities in data/model organization and integration. \;
The meeting will provide a collaborative platform
for PARC modelers and data managers to exchange expertise\, align strateg
ies\, and enhance synergy between different work packages. This event will
be instrumental in shaping the future of modeling within PARC\, fostering
interdisciplinary collaboration\, and driving innovation in chemical risk
assessment. Participants are encouraged to contribute actively to discuss
ions and knowledge-sharing sessions.
\;
\;
X-MICROSOFT-CDO-ALLDAYEVENT:TRUE
DTSTAMP:20260430T194900Z
END:VEVENT
BEGIN:VEVENT
UID:69f3b22c446be
DTSTART;VALUE=DATE:20250611
SEQUENCE:0
TRANSP:OPAQUE
DTEND;VALUE=DATE:20250612
SUMMARY:PARC Modelers'\; Meeting – Advancing Chemical Risk Assessment
through Modeling
CLASS:PUBLIC
DESCRIPTION:The PARC Modelers' Meeting will bring together modelers and dat
a managers from multiple PARC work packages and related activities. This i
nternal meeting aims to review progress\, discuss future directions\, and
strengthen collaborations in the field of chemical risk assessment modelin
g. \;The meeting will focus on five core modeling areas: \;Physiol
ogically Based Kinetic (PBK) Models – Covering both toxicokinetic and ph
armacokinetic modeling.Quantitative Structure-Activity Relationships (QSAR
) – Exploring modern machine learning and artificial neural network appr
oaches.Artificial Intelligence (AI) in Chemical Risk Assessment (CRA) –
Examining AI applications beyond QSAR in CRA.Exposure Models – Discussin
g advancements in exposure modeling techniques.Data Management – Address
ing challenges and opportunities in data/model organization and integratio
n. \;The meeting will provide a collaborative platform for PARC modele
rs and data managers to exchange expertise\, align strategies\, and enhanc
e synergy between different work packages. This event will be instrumental
in shaping the future of modeling within PARC\, fostering interdisciplina
ry collaboration\, and driving innovation in chemical risk assessment. Par
ticipants are encouraged to contribute actively to discussions and knowled
ge-sharing sessions. \; \;
X-ALT-DESC;FMTTYPE=text/html:The PARC Modelers' Meeting will bring toge
ther modelers and data managers from multiple PARC work packages and relat
ed activities. This internal meeting aims to review progress\, dis
cuss future directions\, and strengthen collaborations in the fie
ld of chemical risk assessment modeling. \;
The meeting will focus on five core modeling areas: \;
Physiologically Based Kinetic (PBK) Models – Cove
ring both toxicokinetic and pharmacokinetic modeling.Quan
titative Structure-Activity Relationships (QSAR) – Exploring mo
dern machine learning and artificial neural network approaches.Artificial Intelligence (AI) in Chemical Risk Assessment (CRA) – Examining AI applications beyond QSAR in CRA.Expo
sure Models – Discussing advancements in exposure modeling tech
niques.Data Management – Addressing challenges
and opportunities in data/model organization and integration. \;
The meeting will provide a collaborative platform
for PARC modelers and data managers to exchange expertise\, align strateg
ies\, and enhance synergy between different work packages. This event will
be instrumental in shaping the future of modeling within PARC\, fostering
interdisciplinary collaboration\, and driving innovation in chemical risk
assessment. Participants are encouraged to contribute actively to discuss
ions and knowledge-sharing sessions.
\;
\;
X-MICROSOFT-CDO-ALLDAYEVENT:TRUE
DTSTAMP:20260430T194900Z
END:VEVENT
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