Z Score,T Score, Percential Rank and Box Plot Graph
The Role of ADME ^0 Toxicology Studies S.pptx
1. THE ROLE OF INSILICO ADME &
TOXICOLOGY STUDIES IN DRUG
DISCOVERY & DEVELOPMENT
~ PRANAVI UPPULURI
NATIONAL INSTITUTE OF PHARMACEUTICAL EDUCATION AND RESEARCH, NIPER, HYDERABAD
2. Here we consider…,
2
1. What does ADMET mean? What
does it provide to drug
developers?
2. Why is insilico ADMET
needed?
3. What are Drug like
properties
4. How does ADMET data
obtained?
5. When does ADMET data needed?
6. What ADMET properties do we
need to predict?
7.What computational tools are
used to predict ADMET
8. Summary and Conclusion
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3. WHAT DOES ADMET MEAN?
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Absorption: The Molecular Passport Control
Think of it as the body's border control
system. When a molecule enters, it's like a
traveler showing its ID and going through
security. This marks the start of the
molecule's journey, and it has to pass through
the body's checks smoothly.
Distribution: The Great Odyssey Within
Think of it as a molecule's grand journey
through the body. It's like a heroic odyssey,
where the molecule faces challenges, makes
important stops, and eventually reaches its
destination.
Metabolism: The Biochemical Alchemist
This is like the body's magical transformation
room. Molecules change here, like ingredients
in a cauldron, with enzymes and reactions
shaping them into what the body requires. It's
like the body's unique alchemy, turning
substances into what it needs.
Excretion: The Silent Exit
This is how molecules gracefully leave the
body once their job is done, much like a
discreet actor exiting the stage without the
audience noticing. It's all about maintaining
the body's delicate balance by not overstaying
their welcome.
Toxicity: The Dark Side Unveiled
It's like a hidden antagonist in the body's
story, waiting to disrupt its harmony. Similar
to a masked villain, it only shows its true
nature when provoked, potentially causing
chaos and conflict in the carefully planned
narrative of the body.
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4. 1. Absorption – How much of the drug is
absorbed and how quickly?
(bioavailability)
2. Distribution- Where is the drug
distributed within the body? What is the
rate and extent of the distribution?
3.Metabolism- How fast is the drug
metabolized? What is the mechanism of
action? What metabolite is formed and is
it active or toxic?
4. Elimination- How is the drug excreted
and how quickly?
5.Toxicity-Does this drug have a toxic
effect to body systems or organs?
WHAT DOES' ADMET STUDIES PROVIDE TO DRUG DEVELOPERS?
These studies help to determine the viability of a drug candidate by answering these key questions:
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5. WHY IS IN SILICO ADMET NEEDED?
Cost-Efficiency
Risk Mitigation and Early-Stage Decision Making
Data-Driven Decision-Making
Rapid Screening of potential hits
Ethical Considerations
Regulatory Compliance
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6. 6
Fig 1: The evolution of drug discovery and the changing role of ADME studies.
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7. 7
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Fig 2: An analysis of the main reasons for
attrition in drug development…., half of
all failures were attributed to poor
pharmacokinetics (39%) and animal toxicity
(11%)
8. DRUG-LIKE PROPERTIES
LIPINSKI’S RULE
1. No.of H2 bond donors <= 5
2. No.of H2 bond acceptors <= 10
3. Molecular weight <= 500
4. cLogP <= 5
MDDR LIKE RULES
1. No. of rings >=3
2. No.of rigid bonds >= 18
3. No.of rotatable bonds >= 6
VEBER RULE
1. Rotatable bond count <= 10
2. PSA <= 140
GHOSE FILTER
1. logP( -0.4 to 5.6)
2. MR ( 40 to 130)
3. MW( 160 TO 480)
4. PSA < 140
5. No.of atoms (20 to 70)
CMC 50 LIKE RULE
1. MR (70 to 110)
2. MW(230 to 390)
3. No.of atoms (30 to 55)
4. AlogP (1.3 to 4.1)
BBB RULE
1. H-Bonds (8 to 10)
2. MW
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9. 1. In vitro methods 2. In vivo methods
3. Predictive
models/Insilico
methods
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HOW DOES ADMET DATA OBTAINED?
The quest for early, fast, and relevant ADMET data is tackled in three ways
10. Pranavi Uppuluri 10
WHEN DOES ADMET DATA NEEDED?
1. Early Discovery:
Identifying promising drug
candidates.
2. Lead Optimization:
Refining compounds for better
profiles.
3. Candidate Selection:
Prioritizing candidates for
development.
4. Preclinical & Clinical:
Informing study designs.
5. Regulatory Submissions:
Essential for drug approvals.
6. Post-Market Surveillance:
Ensuring ongoing safety.
7. Drug Repurposing:
Assessing suitability for new
uses.
11. WHAT ADME PROPERTIES DO WE WANT TO PREDICT?
We need to predict the properties that provides the information about…,
Half-life (T1/2)
Hepatic Clearance
Renal Clearance
Cytochrome P450 Interactions
Metabolic Identification
Metabolic Stability
Volume of distribution
Plasma Protein Binding
Transport Interactions
Permeability
Bioavailability
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12. 12
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Fig 3: This figure does not
suggest a logical flow in
ADME studies, but rather
tries to group the problem
areas for which predictive
models could be of help
19. IN SILICO PREDICTION OF TOXICITY ISSUES
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The existing commercially available in silico tools for forecasting potential
toxicity issues must primary emphasis is on carcinogenicity and mutagenicity,
teratogenicity, irritation, sensitization, immunotoxicology and neurotoxicity.
There is currently an unmet need for in silico predictive toxicology software
for other end-points important in drug development, such as QT prolongation,
hepatotoxicity and phospholipidosis
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20. SUMMARY
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No single approach can be used to predict the full range of ADME
properties that are desired. A challenge in this field is to identify
the technique that is most suitable for modelling the property under
investigation.
In fact, a combination of two or more models for the same property,
based on different principles, can give higher confidence in the results
obtained for which they agree or identify areas of uncertainty where
they differ.
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21. REFERENCE:
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1. van de Waterbeemd, H., Gifford, E. ADMET
in silico modelling: towards prediction
paradise?. Nat Rev Drug Discov 2, 192–204
(2003). https://doi.org/10.1038/nrd1032
2. Schyman, P., Liu, R., Desai, V. and
Wallqvist, A., 2017. vNN web server for
ADMET predictions. Frontiers in
pharmacology, 8, p.889.
3. Guan, L., Yang, H., Cai, Y., Sun, L., Di,
P., Li, W., Liu, G. and Tang, Y., 2019.
ADMET-score–a comprehensive scoring function
for evaluation of chemical drug-
likeness. Medchemcomm, 10(1), pp.148-157.
4. O'Brien, S.E. and de Groot, M.J., 2005.
Greater than the sum of its parts: combining
models for useful ADMET prediction. Journal
of medicinal chemistry, 48(4), pp.1287-1291.
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