This document discusses therapeutic drug monitoring for digoxin. Digoxin is used to treat heart conditions like congestive heart failure and arrhythmias. It works by inhibiting the sodium-potassium pump in cardiac cells. Therapeutic drug monitoring is important due to digoxin's narrow therapeutic index and interactions with other drugs and conditions that can impact its levels. The therapeutic range is 0.8-2 ng/ml. Samples should be taken at least 8 hours after administration to allow for distribution. Dosing is calculated based on factors like renal function and weight. Levels are monitored to confirm toxicity, assess noncompliance or treatment failure, and evaluate factors altering pharmacokinetics.
Digoxin & Nitroglycerin by Dr. Sanaullah Aslam (Complete)Sanaullah Aslam
Your Feedback will be highly appreciated. This presentation was made for students at pharmacy institute in a project of clinical pharmacy and use of digoxin and nitroglycerin. This presentation is made so that you can present it in a same session, without any change.
Myocardial Infarction Treatment
Classes of drugs used in the treatment of myocardial infarction
Vasodilators
General Pharmacology
Cardiac depressant drugs
Antiarrhythmics
Anti-thrombotics
Thrombolytics
Analgesics
General Mechanisms of Action
Digoxin & Nitroglycerin by Dr. Sanaullah Aslam (Complete)Sanaullah Aslam
Your Feedback will be highly appreciated. This presentation was made for students at pharmacy institute in a project of clinical pharmacy and use of digoxin and nitroglycerin. This presentation is made so that you can present it in a same session, without any change.
Myocardial Infarction Treatment
Classes of drugs used in the treatment of myocardial infarction
Vasodilators
General Pharmacology
Cardiac depressant drugs
Antiarrhythmics
Anti-thrombotics
Thrombolytics
Analgesics
General Mechanisms of Action
Pharmacokinetic concepts and principles in humans in order to design individualized dosage regimens which optimize the therapeutic response of a medication while minimizing the chance of an adverse drug reaction.
Therapeutic Drug Monitoring (TDM)
Discuss the logic for therapeutic drug monitoring, which refer to as (TDM)
List various classes of drugs that require TDM
General description of this therapeutic drag TD
Discuss the proper sample timing and method for TDM
And Discuss analytical methods available for TDM
List various drugs that not require TDM
Steady state
Therapeutic Drug Groups
Digoxin, quinidine, procainamide, disopyramide.
- Aminoglycosides (amikacin, gentamicin, kanamycin, tobramycin) - vancomycin
leucovorin rescue ?
First-pass metabolism
HPLC methods
Seminar of U.V. Spectroscopy by SAMIR PANDASAMIR PANDA
Spectroscopy is a branch of science dealing the study of interaction of electromagnetic radiation with matter.
Ultraviolet-visible spectroscopy refers to absorption spectroscopy or reflect spectroscopy in the UV-VIS spectral region.
Ultraviolet-visible spectroscopy is an analytical method that can measure the amount of light received by the analyte.
Multi-source connectivity as the driver of solar wind variability in the heli...Sérgio Sacani
The ambient solar wind that flls the heliosphere originates from multiple
sources in the solar corona and is highly structured. It is often described
as high-speed, relatively homogeneous, plasma streams from coronal
holes and slow-speed, highly variable, streams whose source regions are
under debate. A key goal of ESA/NASA’s Solar Orbiter mission is to identify
solar wind sources and understand what drives the complexity seen in the
heliosphere. By combining magnetic feld modelling and spectroscopic
techniques with high-resolution observations and measurements, we show
that the solar wind variability detected in situ by Solar Orbiter in March
2022 is driven by spatio-temporal changes in the magnetic connectivity to
multiple sources in the solar atmosphere. The magnetic feld footpoints
connected to the spacecraft moved from the boundaries of a coronal hole
to one active region (12961) and then across to another region (12957). This
is refected in the in situ measurements, which show the transition from fast
to highly Alfvénic then to slow solar wind that is disrupted by the arrival of
a coronal mass ejection. Our results describe solar wind variability at 0.5 au
but are applicable to near-Earth observatories.
A brief information about the SCOP protein database used in bioinformatics.
The Structural Classification of Proteins (SCOP) database is a comprehensive and authoritative resource for the structural and evolutionary relationships of proteins. It provides a detailed and curated classification of protein structures, grouping them into families, superfamilies, and folds based on their structural and sequence similarities.
Introduction:
RNA interference (RNAi) or Post-Transcriptional Gene Silencing (PTGS) is an important biological process for modulating eukaryotic gene expression.
It is highly conserved process of posttranscriptional gene silencing by which double stranded RNA (dsRNA) causes sequence-specific degradation of mRNA sequences.
dsRNA-induced gene silencing (RNAi) is reported in a wide range of eukaryotes ranging from worms, insects, mammals and plants.
This process mediates resistance to both endogenous parasitic and exogenous pathogenic nucleic acids, and regulates the expression of protein-coding genes.
What are small ncRNAs?
micro RNA (miRNA)
short interfering RNA (siRNA)
Properties of small non-coding RNA:
Involved in silencing mRNA transcripts.
Called “small” because they are usually only about 21-24 nucleotides long.
Synthesized by first cutting up longer precursor sequences (like the 61nt one that Lee discovered).
Silence an mRNA by base pairing with some sequence on the mRNA.
Discovery of siRNA?
The first small RNA:
In 1993 Rosalind Lee (Victor Ambros lab) was studying a non- coding gene in C. elegans, lin-4, that was involved in silencing of another gene, lin-14, at the appropriate time in the
development of the worm C. elegans.
Two small transcripts of lin-4 (22nt and 61nt) were found to be complementary to a sequence in the 3' UTR of lin-14.
Because lin-4 encoded no protein, she deduced that it must be these transcripts that are causing the silencing by RNA-RNA interactions.
Types of RNAi ( non coding RNA)
MiRNA
Length (23-25 nt)
Trans acting
Binds with target MRNA in mismatch
Translation inhibition
Si RNA
Length 21 nt.
Cis acting
Bind with target Mrna in perfect complementary sequence
Piwi-RNA
Length ; 25 to 36 nt.
Expressed in Germ Cells
Regulates trnasposomes activity
MECHANISM OF RNAI:
First the double-stranded RNA teams up with a protein complex named Dicer, which cuts the long RNA into short pieces.
Then another protein complex called RISC (RNA-induced silencing complex) discards one of the two RNA strands.
The RISC-docked, single-stranded RNA then pairs with the homologous mRNA and destroys it.
THE RISC COMPLEX:
RISC is large(>500kD) RNA multi- protein Binding complex which triggers MRNA degradation in response to MRNA
Unwinding of double stranded Si RNA by ATP independent Helicase
Active component of RISC is Ago proteins( ENDONUCLEASE) which cleave target MRNA.
DICER: endonuclease (RNase Family III)
Argonaute: Central Component of the RNA-Induced Silencing Complex (RISC)
One strand of the dsRNA produced by Dicer is retained in the RISC complex in association with Argonaute
ARGONAUTE PROTEIN :
1.PAZ(PIWI/Argonaute/ Zwille)- Recognition of target MRNA
2.PIWI (p-element induced wimpy Testis)- breaks Phosphodiester bond of mRNA.)RNAse H activity.
MiRNA:
The Double-stranded RNAs are naturally produced in eukaryotic cells during development, and they have a key role in regulating gene expression .
The increased availability of biomedical data, particularly in the public domain, offers the opportunity to better understand human health and to develop effective therapeutics for a wide range of unmet medical needs. However, data scientists remain stymied by the fact that data remain hard to find and to productively reuse because data and their metadata i) are wholly inaccessible, ii) are in non-standard or incompatible representations, iii) do not conform to community standards, and iv) have unclear or highly restricted terms and conditions that preclude legitimate reuse. These limitations require a rethink on data can be made machine and AI-ready - the key motivation behind the FAIR Guiding Principles. Concurrently, while recent efforts have explored the use of deep learning to fuse disparate data into predictive models for a wide range of biomedical applications, these models often fail even when the correct answer is already known, and fail to explain individual predictions in terms that data scientists can appreciate. These limitations suggest that new methods to produce practical artificial intelligence are still needed.
In this talk, I will discuss our work in (1) building an integrative knowledge infrastructure to prepare FAIR and "AI-ready" data and services along with (2) neurosymbolic AI methods to improve the quality of predictions and to generate plausible explanations. Attention is given to standards, platforms, and methods to wrangle knowledge into simple, but effective semantic and latent representations, and to make these available into standards-compliant and discoverable interfaces that can be used in model building, validation, and explanation. Our work, and those of others in the field, creates a baseline for building trustworthy and easy to deploy AI models in biomedicine.
Bio
Dr. Michel Dumontier is the Distinguished Professor of Data Science at Maastricht University, founder and executive director of the Institute of Data Science, and co-founder of the FAIR (Findable, Accessible, Interoperable and Reusable) data principles. His research explores socio-technological approaches for responsible discovery science, which includes collaborative multi-modal knowledge graphs, privacy-preserving distributed data mining, and AI methods for drug discovery and personalized medicine. His work is supported through the Dutch National Research Agenda, the Netherlands Organisation for Scientific Research, Horizon Europe, the European Open Science Cloud, the US National Institutes of Health, and a Marie-Curie Innovative Training Network. He is the editor-in-chief for the journal Data Science and is internationally recognized for his contributions in bioinformatics, biomedical informatics, and semantic technologies including ontologies and linked data.
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...Sérgio Sacani
We characterize the earliest galaxy population in the JADES Origins Field (JOF), the deepest
imaging field observed with JWST. We make use of the ancillary Hubble optical images (5 filters
spanning 0.4−0.9µm) and novel JWST images with 14 filters spanning 0.8−5µm, including 7 mediumband filters, and reaching total exposure times of up to 46 hours per filter. We combine all our data
at > 2.3µm to construct an ultradeep image, reaching as deep as ≈ 31.4 AB mag in the stack and
30.3-31.0 AB mag (5σ, r = 0.1” circular aperture) in individual filters. We measure photometric
redshifts and use robust selection criteria to identify a sample of eight galaxy candidates at redshifts
z = 11.5 − 15. These objects show compact half-light radii of R1/2 ∼ 50 − 200pc, stellar masses of
M⋆ ∼ 107−108M⊙, and star-formation rates of SFR ∼ 0.1−1 M⊙ yr−1
. Our search finds no candidates
at 15 < z < 20, placing upper limits at these redshifts. We develop a forward modeling approach to
infer the properties of the evolving luminosity function without binning in redshift or luminosity that
marginalizes over the photometric redshift uncertainty of our candidate galaxies and incorporates the
impact of non-detections. We find a z = 12 luminosity function in good agreement with prior results,
and that the luminosity function normalization and UV luminosity density decline by a factor of ∼ 2.5
from z = 12 to z = 14. We discuss the possible implications of our results in the context of theoretical
models for evolution of the dark matter halo mass function.
This pdf is about the Schizophrenia.
For more details visit on YouTube; @SELF-EXPLANATORY;
https://www.youtube.com/channel/UCAiarMZDNhe1A3Rnpr_WkzA/videos
Thanks...!
2. INTRODUCTION
• Digoxin is the primary cardiac glycoside.
• It is used in the
-treatment of CHF because of its
inotropic effects on the myocardium.
- treatment of atrial fibrillation because
of its chronotropic effects.
-treatment of atrial flutter because of its
positive inotropic effects
-treatment paroxysmal atrial tachycardia
because of its positive inotropic effects
3. PHARMACOLOGICAL ACTIVTY
• The positive inotropic effects is caused by the
binding to Na+ K+ ATPase activated adenosine
phosphate → inhibition of Na pump →
decreased transport of Na+ out of myocardial
cells ( increased intracellular conc ) → calcium
entry and decrease calcium elimination →
enhanced myocardial contractility.
6. CLINICAL PHARMACOKINETICS/
PHARMACODYNAMICSCONSIDERATIONS
• Pharmacodynamic considerations for tachyarrhythmias and
systolic heart failure as follows:
Tachyarrhthmias
• Narrow therapeutic range.
• Used to control the ventricular response rate, particular in
CHF.
• Ventricular rate control usually achieved over 24 hours.
• A loading dose given in divided doses because of a long
distribution half-life.
• Possible to use higher doses to control rate in the acute
setting.
7. Systolic heart failure
• Decreases frequency of hospitalization for
exacerbation of heart failure.
• No improvement in cardiovascular mortality.
• Serum concentration achieved in mortality trial
at the lower end of therapeutic range.
• Necessary to maintain serum conc in the mid to
low therapeutic range ( < 1.5 ng/ml ).
• Edema and cardiac output changes with severity
of heart failure may alter pharmacoknetic
parameters.
8. PHARMACOKINETIC CONSIDERATION:
ABSORPTION
• Completely absorbed from the gut.
• In some patients, absorption may be decreased
due to digoxin inactivation by gut bacteria
(Eubacterium lenium).
• Also by some drugs like antacids, cholestyramine,
tetracycline, neomycin and kaolin.
• For patients with normal absorption:
Digoxin tablets: 50-90%
Digoxin elixir: 80%
Digoxin liquid filled capsules: 100%
9. DISTRIBUTION
• Digoxin distributes into lean body tissue but not
appreciably into adipose or fatty tissues.
• For this reason ideal body weight should be used to
dose digoxin.
• 20-30% bound to albumin.
• Vd : 6- 7 l/kg
• Distributive phase is 6 to 8 hour.
• Two clinical implications:
-loading doses of digoxin need to be
administered in divided doses 6 hour apart.
-serum digoxin levels should be determined at
least 8 hr after administration.
10. METABOLISM
• Takes place in stomach and intestine.
• Involves :
Deglycosylation
Reduction of the lactone ring
Oxidation
Epimerization
Conjugation to polar metabolites
11. CONTINUE...
• In Stomach,
Gastric acid
removes digitoxose sugars of digoxin
formation of deglycosylated congeners
• In intestine,
Intestinal flora
results in metabolism of digoxin
to its reduced form, dihydrodigoxin
13. ELIMINATION
• Excreted largely unchanged in the urine.
• Small proportion is cleared by nonrenal routes,
biliary excretion and intestinal clearence.
• Vd decreases with decrease in renal function.
• In patients with severe renal dysfunction, 18% of
digoxin is only bound to protein.
Displacement of digoxin by endogenous
substances that are not cleared efficiently in renal
patients
Reduces protein binding by digoxin
14. • Systemic clearance (Clt):
Clt = (1.01 × Clr ) + Clm
Clr = renal clearence
= 0.927 × Cr Cl ( ml/min/1.73 m2 )
Clm = metabolic clearence
= 36 ml /min ÷ 1.73 m2 (in resolved or
no history of heart disease)
= 20 ml /min ÷ 1.73 m2 ( with severe
heart disease)
15. Available dosage forms
Dosage form Tablet
(conventional)
Capsules
(lanoxicaps)
Elixir Parenteral
injection
125 ,250, 500
mcg
50,100,200
mcg
50mcg/ml 100, 250 mcg
/ml
Biovailalability 60-80% 90-100% 60-80% 100%
Tmax There is a significant distribution phase after
administration , even after IV administraton
.Therefore , there is a time lag before maximum
effect.
17. INDICATIONS
• Confirmation of toxicity
• Assessing the effect of factors altering
pharmacokinetics
• Therapeutic failure
• Medication compliance
18. Confirmation of toxicity
• Need to measure digoxin conc for
Confirmation of toxicity due to the low
therapeutic index.
• Therapeutic range: 1.0-2.5 nmol/l
• Risk of toxicity : Over 2.6 nmol/l
19.
20. Assessing the effect of factors altering
pharmacokinetics
• No. of factors influence the pharmacokinetics.
• Renal function is the major contributor.
• Cockroft gault equation will result in an appropriate
dose.
• P-glycoprotein is involved in the transport of digoxin into
the body and out of the body in the renal tubules.
• Mutation within this gene →alter bioavailability and
renal clearence.
• drug interaction → affect serum conc of digoxin by
competitive inhibition of P-glycoprotein.
21. Therapeutic failure
• TDM is useful to detect patients with
-low digoxin conc
-who may benefit from increased dose
-who develop toxicity symptoms from an
increased dose
• Results from the “PROVED” and “RADIANCE” trials,
suggest that digoxin concentrations between 0.6 &
1.2 nmol/l may be efficacious and less pro-
arrythmic ,than conc with heart failure.
22. APPROPRIATE SAMPLING TIME
• Digoxin is well absorbed, with peak serum
conc occurring within one hour.
• Because of large Vd , digoxin concentrates in
the tissues, with the active site within
myocardial and other cells.
• Redistribution from serum to tissue takes at
least 8 hours.
23. Samples taken within 8 hours
falsely shows elevated conc
results in inappropriate dose reduction
thus, measure digoxin conc after 8 hours
(when conc have steady state)
shows linear
24.
25. • Digoxin elimination is predominantly renal in nature
(fraction excreted: 0.6-0.9)
• Depends on glomerular filtration and p-glycoprotein
mediated active tubular secretion.
• A long t1/2 of atleast 30 hour results in steady state
conc taking at least 5 days to be achieved (in normal
renal function patient).
• In the elderly and patients with renal impairment,
elimination is diminished and t1/2 prolonged.
• In this case , steady state may take several weeks to
achieve.
26. DOSE ADJUSTMENT
• When the conc is above the therapeutic
range, the dose should be reduced even in the
absence of obvious toxicity →patient is at risk
of arrhythmias.
• Also, toxicity can occur with conc within the
therapeutic range → result from several
known factors that change tissue sensitivity to
digoxin and alter the therapeutic index.
28. DOSING
• Jeliffe method is a simple method for
calculating loading and maintenance dose.
• Produce dosing regimens that will provide a
serum digoxin level of approx 2.0 ng/ml.
• it is important to adjust the dose empirically if
significant drug-disease or drug-drug
interactions are present.
29. LOADING DOSE ( TOTAL BODY STORES)
LD ( TBS) = (10 mcg/kg)×IBW(kg)
F
• Half of this loading dose is administered
intravenously or orally.
• The remaining dose is divided equally and
administered at 6-h interval (1/2 dose , ¼ dose, ¼
al 6 h intervals).
• This is necessary to account for the slow
distribution , half life of the drug.
30. MAINTENANCE DOSE
• it can be calculated based on the amount of
the loading dose ( TBS) that is eliminated each
day.
% TBS lost daily = 14 + Cl Cr ( ml/min)
5
MD =TBS (% TBS lost each day)
31. • Example:
JL is a 68 year old male who is admitted to the
hospital for atrial fibrillation. During his
hospitalization he is converted to normal sinus
rhythm b quinidine. His past medical history includes
CHF . His thyroid function is normal. His weight is 84
kg (IBW = 73 kg) and his estimated creatinine
clearance is 68 ml/min. what would be an
appropriate oral loading and maintenance dose?
32. • LD = 10 × 73 =TBS = 1043 mcg(1.4 mg)
0.7
Administer 0.5 mg orally, then 0.25 mg in 6 h, then
0.25 mg in 6 h.
MD= TBS (%TBS LOST EACH DAY)
% TBS LOST EACH DAY =14 + 68 ml/min = 27.6%
5
MD = 1.04 mg (27.6%) = 0.29 mg
Because JL is also on quinidine the MD would be
decreased by 50%.
MD = 0.15 or 0.125 mg/day
34. Enzyme Immunoassay ( EIA)
• In this method, the label on the tracer is an
enzyme.
• The catalytic properties of enzymes allows the
detection and quantitation of small quantities of
the drug.
35. Cloned Enzyme Donor Immunoassay
(CEDIA)
• The method uses an antibody to detect the
drug to be measured.
• A label is used to measure the binding reaction.
• It uses genetically engineered fragment of the
enzyme β-galactosidase as the label.
36. Enzyme Multiplied Immunoassay (EMIT)
• The method uses activity as an enzyme glucose
6-phosphate dehydrogenases chemically
coupled to a drug molecule.
• Activity of the enzyme is inhibited when the
drug is bound to a specific antibody.
• The extent of enzyme activity reflects the
proportion of enzyme-labelled drug which is not
bound to antibody, which in turn reflects the no.
of binding sites occupied by unlabelled drug and
hence the drug conc in the sample.
37. Fluorescence Polarisation Immunoassay
(FPIA)
• The method uses specific antibodies to isolate
the desired analyte.
• Small fluorescent molecule, excited with
polarised vertical light, rotates rapidly and
emits polarised light in comparison to
molecules.
• The intensity of polarised light is a measure of
conc of the analyte.
38. ANALYTICAL ISSUES
• Specimens from patients treated with digoxin
antidote give misleading values for digoxin
conc by most immunoassays.
• Biological activities of some metabolites of
digoxin are low relative to the parent
compound.
• One method for measuring the unbound
digoxin →to use ultrafiltration before
immunoassay.
39. Pharmacokinetic parameter and TDM information
PARAMETER VALUE
Elimination half life 36 hrs(adults)
18-37 hrs(children)
Total body clearance(ml/min/kg) 2.7
Volume of distribution ‘V’ 6-7L/kg(total body weight)
Plasma protein binding 20-30%
Therapeutic range 0.9-2 ng/ml for atrial fibrillation
(0.5-1.2 for CHF)
Time to steady state concentration 6-10 days
Loading dose Two 0.5mg oral tablet doses or
Two 0.375mg IV doses, separated by 6
hrs(pts.with creatinine clearance>20ml/min)
0.2 mg/day(creatinine clearance>20 ml/min)
Maintenance dose 0.125 mg/day(clearance <20ml/min or body
weight <40kg)
Clinically important metabolite Bis and mono-digitoxosides
As cardioactive as digoxin