In vivo is the Latin word which means with in the living body. When effects of various biological entities are tested on whole, living organism or cells, usually animals including humans and plants. Animal testing and clinical trials are major elements of in-vivo research. In vivo testing is often employed over in vitro because it is better suited for observing the overall effects of an experiment on a living subject in drug discovery. example, verification of efficacy in vivo is crucial, because in vitro assays can sometimes yield misleading results with drug. Harry Smith found that sterile filtrates of serum from animals infected with Bacillus anthracis were lethal for other animals, whereas extracts of culture fluid from the same organism grown in vitro were not. In microbiology Once cells are disrupted and individual parts are tested or analyzed, this is known as in vitro. In vitro studies within the glass, i.e., in a laboratory environment using test tubes, petri dishes, etc. Examples of investigations in vivo include: the pathogenesis of disease. In vitro toxicology:- The bridge exists between new drug discovery and drug development.- Provide information on mechanism of action of a drug Provides an early indication of the potential for some kinds of toxic effects, allowing a decision to terminate or to proceed further. In vitro methods are widely used for:- Screening and ranking chemicals Get a platform for animal studies for physiological actions Studying cell, tissue, or target specific effects Improve subsequent study design Advantages and Disadvantages:- Faster than in vivo studies Less expensive to run Less predictive of toxicity in intact organisms In vitro to in vivo extrapolation (IVIVE) refers to the qualitative or quantitative transposition of experimental results or observations made in vitro to predict phenomena in vivo, biological organisms. The problem of transposing in vitro results is particularly acute in areas such as toxicology where animal experiments are being phased out and are increasingly being replaced by alternative tests. Results obtained from in vitro experiments cannot often be directly applied to predict biological responses of organisms to chemical exposure in vivo. Therefore, it is extremely important to build a consistent and reliable in vitro to in vivo extrapolation method. Two solutions are now commonly accepted: Increasing the complexity of in vitro systems where multiple cells can interact with each other in order recapitulate cell-cell interactions present in tissues (as in "human on chip" systems). Using mathematical modeling to numerically simulate the behavior of a complex system, whereby in vitro data provides the parameter values for developing a model. The two approaches can be applied simultaneously allowing in vitro systems to provide adequate data for the development of mathematical models. To comply with push for the development of alternative testing methods.

1. EXTRAPOLATION OF IN VITRO DATA TO
PRECLINICAL
A
PRESENTATION
OF
MASTER OF PHARMACY
IN
PHARMACOLOGY
SUBJECT CODE - MPL103T
SUBJECT NAME- TOXICOLOGY 1
DEPARTMENT OF PHARMACOLOGY
TEERTHANKER MAHAVEER COLLEGE OF PHARMACY
TEERTHANKER MAHAVEER UNIVERSITY
MORADABAD
SESSION: 2022-2023
SUBMITTED TO
PROF. PHOOLCHANDRA
SUBMITTED BY
PRAKHAR VARSHNEY

2. In vivo studies
 In vivo is the Latin word which means with in the living body.
 When effects of various biological entities are tested on whole, living organism or cells, usually animals
including humans and plants.
 Animal testing and clinical trials are major elements of in-vivo research.
 In vivo testing is often employed over in vitro because it is better suited for observing the overall effects of
an experiment on a living subject in drug discovery.
 example, verification of efficacy in vivo is crucial, because in vitro assays can sometimes yield misleading
results with drug.
 Harry Smith found that sterile filtrates of serum from animals infected with Bacillus anthracis were lethal
for other animals, whereas extracts of culture fluid from the same organism grown in vitro were not.
 In microbiology Once cells are disrupted and individual parts are tested or analyzed, this is known as in
vitro.
In vitro studies
 In vitro studies within the glass, i.e., in a laboratory environment using test tubes, petri dishes, etc.
Examples of investigations in vivo include: the pathogenesis of disease.

3. In vitro toxicology:-
 The bridge exists between new drug discovery and drug development.-
 Provide information on mechanism of action of a drug
 Provides an early indication of the potential for some kinds of toxic effects, allowing a decision to terminate or to
proceed further.
In vitro methods are widely used for:-
 Screening and ranking chemicals
 Get a platform for animal studies for physiological actions
 Studying cell, tissue, or target specific effects
 Improve subsequent study design
Advantages and Disadvantages:-
 Faster than in vivo studies
 Less expensive to run
 Less predictive of toxicity in intact organisms

4. Preclinical trials:-
A laboratory test of a new drug or a series of chemicals, usually done on animal subjects, to see if the hoped-for
treatment really works and if it is safe to test on humans.
Several steps of preclinical trials:-
Identify a Drug
Target
Develop
a Bioassay
Screen the
Drug in the
Assay
Establish
Effective and
Toxic Doses
File for
approval as an
Investigational
New Drug
(IND)

5. Preclinical studies
In vitro In vivo
Pharmacologica
l studies
Efficacy
Dose
conversion
Determination of
starting dose
Toxicological
studies
Safety
 Receptor Characterization
 Receptor binding assay
 Enzyme inhibition
 2° Messenger analysis
 Cytotoxic activity
A route map of
preclinical studies

7. Preclinical Research can fall short in 3 ways:-
1. Failure to predict human risks
2. Clinical benefits that fail to materialize in humans
3. Prediction of non-existent risks in humans
Extrapolation of in vitro data to preclinical to humans:-
Estimating the first in human (FIH) dose is one of the initial steps in the clinical development of any molecule
that has successfully gone through all of the hurdles in preclinical evaluations.

8. MABEL is the ”anticipated dose level leading to minimal biological effect level in humans”. In general, MABEL can be
used to determined a starting dose when conventional toxicology testing may not be sufficient to predict serious adverse
reactions in clinical trials.
NOAEL No-Observed-Adverse-Effect Level:- The no observed adverse effect level is defined as the highest dose where the
effects observed in the treated group do not imply an adverse effect to the subject
LOAEL lowest observed adverse effect level is defined as the lowest dose where the effects observed in the treated group
imply an adverse effect to the subject

9. Calculations based on:
1) Animal pharmacokinetic
2) Administered doses
3) Observed toxicity
4) Algorithmic calculation

10. ESTIMATING THE MRSD-METHODS (maximum recommended starting dose)
1) NOAEL Method
2) MABEL Method.
3) Similar Drug Comparison Method
4) Pharmacokinetic Guided Approach
5) PK/PD Modelling Guided Approach
NOAEL method:- The NOAEL method is based on selecting a dose with minimal risk of toxicity, rather than
selecting one with minimal pharmacologic activity in humans
Steps using animal toxicology data:
1) Determine No Observed Adverse Effect Level (NOAEL) %0
2) Convert NOAEL to Human Equivalent Dose (HED) %0
3) Select most appropriate species %0
4) Apply Safety Factor %0
5) Consider Pharmacologically Active Dose
STEP 1:
NO OBSERVED ADVERSE EFFECT LEVEL DETERMINATION The NOAEL is a generally accepted benchmark for
safety when derived from appropriate animal studies

11. STEP 2:
HUMAN EQUIVALENT DOSE CALCULATION.
After the NOAELS in the relevant animal studies have been determined, they are converted to human equivalent doses
(HEDS) using appropriate scaling factors. The most appropriate method for extrapolating the animal dose to the
equivalent human dose should be decided.
doses scaled (1:1) between species when doses are normalized to body surface area (mg/m²).
These are recommended as the standard values to be used for interspecies dose conversions for NOAELS.
HED = Animal NOAEL x (W animal/W human)(1-b)
Conversion factors = (W animal/W human)(1-b)
Conventionally, for a mg/m² normalization b would be 0.67, but studies have shown that MTDs scale
best across species when b=0.75
Conversion factors are calculated over a range of animal and human weights using (W animal/W
human)0.330r (W animal/W human o.25 to assess the effect on starting dose selection of using b = 0.75
instead of b = 0.67
BASIS FOR USING Mg/Kg CONVERSIONS.
The "mg/kg" scaling will give a 12-,6- & 2-fold higher HED than the default mg/m² approach for
mice, rats, and dogs, respectively
mg/m² = km x mg/kg
where km = 100/K x W0.33 where K is a value unique to each species

12. STEP 3: MOST APPROPRIATE SPECIES SELECTION
Factors that could influence the choice of the most appropriate species. Differences in the absorption, distribution,
metabolism, and excretion (ADME) of the therapeutic between the species
STEP 4: APPLICATION OF SAFETY FACTOR
STEP 5: CONSIDERATION OF THE PHARMACOLOGICALLY ACTIVE DOSE(PAD)
Categories Evaluated in First In Human Trials:-
 Local tolerance studies
 Genotoxicity studies
 Carcinogenicity studies
 Reproduction toxicity studies
 Photo safety testing
 Nonclinical abuse liability
 Other toxicity studies
 Clinical trials in paediatric populations
 Combination drug toxicity testing
 Immunotoxicity

13. MABEL Method:-
• TheMABEListheanticipateddoselevelleadingto aminimal biological effect level in humans.
• In general, MABELcan be used to determined a starting dose when conventional toxicology testing may not
be sufficient to predict serious adverse reactions inclinical trials.
• Proposed by the Association of the British Pharmaceutical Industry (ABPI)/Bioindustry Association
(BIA) Early Stage Clinical Trial Task Force (2006)
• Relativelysafedosewithsomelevelofpharmacologyactivity
• No single method for calculation
• Use all available data
• Binding endpoints (e.g.,bindingaffinity, receptor occupancy)
• Functional endpoints (e.g., cytotoxicity, cytokine release, immune cell activation, intracellular
signaling)

14. MABEL General Factors to Consider:-
1. Mode of action
Novelty of pharmaceutical and target
Plausibility and extent of knowledge of MOA
Concentration/dose response
2. Pharmacology of the target
Tissue distribution and pharmacology of the target in normal and pathological states
3. Relevance of animal models
Compare available data in animals species to humans
Degree of species-selectivity for both target binding and FcyR binding
4.Patient population
Minimize dosing at sub-therapeutic levels in patients

15. Calculating aMABEL
• ThereisnouniversalapproachfordeterminingaFIHdosebasedona MABEL
• Examples for supporting data:
Invitropharmacologydatafromtargetcellsfromhumanandtoxicology species
Evaluation of MOA (agonistic vs antagonistic activity), potential for cytokine release, receptor occupancy,
concentration response data
If using animal data, then provide a comparison of
• Animal-human differences in exposure/drug distribution, differences in expressionlevelanddistributionoftarget,
andaffinityoftargetbinding and intrinsic efficacy
• Duration and reversibility of biologic effect
• Dose-exposure relationship (PK/PD)
Clinical ProtocolConsiderations:-
• Clinical trial population
• Number ofsubjects per cohort (e.g.,single-patientcohorts at potentially sub- therapeutic levels)
• Timeinterval between dosingsubjects withinthesame cohort (e.g., staggered enrollments within cohort)
• Doseescalationincrements(e.g.,acceleratedtitrationmaybeacceptableon a case-by-case basis)
• Criteria andtime interval for escalation tonext cohort (e.g.,extended observation period for dose limitingtoxicities)
• Clinicaltrialsite(availability oftreatments formedicalemergencies and intensive care unit facilities)

16. Animal preclinical
test
Ethics committee
approval
National authority
notification
First-in-man
clinical trials
PROCESS OF EVALUATION OF DATA
EU first-in-man approval steps
7 months from first communication to certification approval

17. Methods of scaling drugs (methods of extrapolation of data)
1. Linear extrapolation/simple scaling/isometric scaling method
2. Non linear extrapolation/allometric scaling method
1. Linear extrapolation:-
mg/kg dose established for one species is applied across all species.
Advantage:-
• Simple
• Dosage and weight are directly (linearly) proportional.
• Problems arise when this method is applied to other species
• This method assumes that any differences in species PK/PD are not clinically relevant
Drawbacks:-
• This method tends to overdose large animals and underdose small animals, which may be very clinically significant.
• Typically, this method is only effective with drugs that have large margins of safety and wide therapeutic ranges.

18. 2. Allometric scaling:-
• Drug pharmacokinetics has a nonlinear (allometric) relationship to weight.
• Allometric scaling has become the method of choice for inter species extrapolation in drug discovery and
development.
• It is the study of size and its consequences Based on the principle that major physiologic processes are
related to body weight raised to allometric exponent
Interspecies difference between PK phase:-
 Body metabolic rate
 Species difference (size independent)
 Rate of drug distribution
 Protein binding
 Drug metabolism
 Drug elimination

19. In vitro to in vivo extrapolation (IVIVE) refers to the qualitative or quantitative transposition of experimental results or
observations made in vitro to predict phenomena in vivo, biological organisms.
The problem of transposing in vitro results is particularly acute in areas such as toxicology where animal experiments are
being phased out and are increasingly being replaced by alternative tests.
Results obtained from in vitro experiments cannot often be directly applied to predict biological responses of organisms to
chemical exposure in vivo.
Therefore, it is extremely important to build a consistent and reliable in vitro to in vivo extrapolation method.
Two solutions are now commonly accepted:
• Increasing the complexity of in vitro systems where multiple cells can interact with each other in order recapitulate cell-
cell interactions present in tissues (as in "human on chip" systems).
• Using mathematical modeling to numerically simulate the behavior of a complex system, whereby in vitro data provides
the parameter values for developing a model.
The two approaches can be applied simultaneously allowing in vitro systems to provide adequate data for the development
of mathematical models. To comply with push for the development of alternative testing methods, increasingly
sophisticated in vitro experiments are now collecting numerous, complex, and challenging data that can be integrated into
mathematical models

20. THANK YOU