Cell Bio Cellular Models for Drug Discovery Flashcards

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1
Q

a brief overview of drug discovery

A
  • ongoing field of study
  • for one drug eventually clinically used - ~6000-10,000 new chemical compounds are synthesized (available for potential preclinical screening)
  • not done in patients –> lab testing (cells)
  • from time target drug is identified ~12 more years until used clinically
  • total cost ~$1 billion - ~half in lab research; ~half in clinical trails
  • for one drug successfully clinically trialed ~19 have failed clinical trials

*can we do better safely?

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2
Q

model systems - example criteria

A
  • “druggable” target
  • pick a model with target that can show a suitable response
  • validate the target/model combo as an appropriate stand-in
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3
Q

What are scientifically, ethically, fiscally, medically & pharmacologically appropriate stand-ins (models) for patients eventually treated with the medications?

A

model systems

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4
Q

druggable” target

A

*biological identity that interacts with a drug

  • a receptor activated by binding insulin –> diabetes
  • an enzyme inhibited by ibuprofen –> inflammation
  • microtubules affected by taxol –> cancer metastasis (assay) before animal + clinical tests
  • just want to know physical association = what is the appropriate model
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5
Q

pick a model with target that can show a suitable response

A
  • how do you test binding of insulin derivative to receptor?
  • what’s a valid model for testing enzyme inhibition?
  • what’s needed to test new anti-metastasis drug?
  • will any one preclinical test prove efficacy of new drug?
  • ex. if we only want to know Kd vs. if we want to turn that into biological response of glucose uptake

*scientific readout you want

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6
Q

validate the target/model combo as an appropriate stand-in

A
  • does model have relevant target regarding delivery, metabolism, binding of drug?
  • can you simplify/downsize/reduce use of typical research models (lab mice/rats etc.)
  • thousands to be tested

*increase throughput

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7
Q

drug discovery models

A

*fish, flies, fungus, & farmacy

  • zebra fish
  • drosophila (fruit fly)
  • yeast (fungus)
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8
Q

zebra fish

A
  • pre-clinical drug discovery
  • easy to monitor embryogenesis, vertebrate cell physiology & gene homologues, small adult size (~1.5 in) allows hi thru-put
  • b-amyloid (alzheimer’s-associated) protein –> defective movement
  • in aquarium, small so many fit, similar vertebrae model
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9
Q

drosophila (fruit fly)

A
  • before clinical testing with people
  • numerous behavior & physiology mutants mapped to specific genes, numerous human gene-equivalents identified
  • Parkinson’s-associated gene –> loss of dopaminergic neurons
  • model nerve degeneration = monitor flight patter, etc. to reflect motor neuron function
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10
Q

yeast (fungus)

A
  • extreme example
  • eukaryote with metabolism mapped to conserved genes
  • SBDS protein associated with bone marrow failure in humans; protein function was unknown
  • a study in yeast showed protein’s function crucial for ribosome function providing a “druggable” target to improve the translation
  • model stands in for bone marrow
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11
Q

human cells in petri dishes as models

A
  • ~45 years ago
  • sensitivity of human cancer cells to anticancer drugs in petri dish tests was directly related to drug success in treating patient tumor
  • does not always occur this way
  • at least for the compounds tested
  • NOT a universally guaranteed approach; that is part of the validation process
  • depends on cancer type, drug, etc.
  • how did we get to that point?
  • how do we go beyond it to make improvements?
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12
Q

cell culture in the 1950’s

A
  • get cells to replicate in lab
  • henrietta lacks & george gey
  • cervical carcinoma cells attached to test tube, mitotically active, split to additional tubes (hela cells)
  • 1st continuous human cell line
  • her cells were immortal and perpetuated
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13
Q

cell culture in 2020

A

cultured cells from diverse sources in addition to sometimes patient tissue

  • if you can get them to grow in petri-dish environment
  • hela and 100’s of other cancer-derived and normal tissue-derived cell types (muscle, skin, cardiac, liver, etc.) used in hi thru put metabolism studies, cancer gene identification, gene sequencing, pre-clinical drug testing
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14
Q

Imetelstat example of preclinical studies for drug effectiveness

A
  • imetelstat inhibits telomerase (RNA/DNA) and stops cell growing, which decreases cells in petri dish
  • imetelstat treated plate slows growth of cancer cells –> cancer cell growth inhibited in presence of antisense oligo imetelstat
  • sense oligo is the same length/sequence but it cannot interact with RNA template –> cancer cells grow in presence of control (sense) oligo
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15
Q

tying topics together

A

tying topics together

  • DNA replication & telomerase
  • cells in culture (petri dish) for testing of new cancer drugs
  • cancer stem cells (to come later in semester)

*normal stem cells need telomerase (no replication senescence)

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16
Q

addressing thru-put - petri dishes

A
  • 6000-10,000 new potential drugs per year (many chemicals to screen)
  • need to increase thru-put for repeats, different concentrations (dose-response), different exposure times
  • downsize to gelatin drop with cells, nutrients (glucose), and test compounds “printed” on microscope slide
  • reduces amount needed of test compound, target cells, cost
17
Q

designing the cell culture model

A

*interpret what happens to cells

  • what cells?
  • what’s to be determined?
  • what scale of testing is to be done?
18
Q

What cells?

A

*do they appropriately model target?

  • normal and cancer cells (test on normal to see if you want to treat cancer –> if it is toxic it might be bad)
  • validate cells retain relevant processes (ex. cyp450 enzymes)
  • demonstrate target is present (ex. receptor)
19
Q

What’s to be determined?

A

*what’s the endpoint

  • survival (maintain number) and/or replication (increase number) - test with neutral red
  • metabolism (biotransformation, ex. in liver) of drug
  • cell migration, intracellular movement
  • cell death (necrosis vs. apoptosis); toxicity - test with neutral red (lethal effect)
20
Q

What scale of testing is to be done?

A
  • biological repeats within assay
  • technical repeats of entire assay
  • varied times of exposure (many days)
  • dose - response correlation
  • cell biol meets bio-engineering

*each variation expands thru put

21
Q

cell culture - drug testing

A

*neutral red (NR) assay - lysosomes

  • NR weak cationic dye - readily penetrates cell membrane
  • more neutral red –> more cells grow with lysosome (healthy)
22
Q

NR in healthy cells

A
  • retained within lysosomes in healthy cells (selectively accumulates)
  • NR binds anionic proteins in lysosome
  • amount is therefore related to cell number
  • assay endpoint; experimentally measure amount of dye
  • replaces counting individual cells
  • dye incorporated into cells is detected visually (microscope) or extraction from cells at end of incubation
  • red dye measured by spectrometry at 540nm
  • dye amount gives quantifiable response to drug
  • lysate cell (break open with red dye) to give an objective number
  • saves time of counting individual lysosomes
23
Q

NR in stressed/damaged lysosome

A
  • dye leaks from stressed/damaged lysosome
  • drug toxic effects stress cell or directly damage lysosome
  • decrease in intracellular (lysosomal) or extractable dye reflects cell damage and/or dying cells
  • less red = less absorbed
24
Q

neutral red (NR) assay - putting it to use

A
  • individual cell (accumulated red) to increase the concentration of candidate drug in cell causes increased damaged cells
  • damaged cells do not spread around the bottom of the well
  • do many times to accumulate repeatable data
  • max redness when all alive (quantitative readout)
25
Q

addressing multiple organ interactions

A
  • most drug delivery ultimately has systemic distribution
  • test new colon cancer drug: drug effects on other organs (possible bone marrow tox) OR other organs (cells) affecting drug? (possible liver metabolism of drug?)
  • cells-on-chip technology = microscale systems biology (organ-on-chip)
  • very small - cells in the chamber (organs) connecting for the circulatory system
  • -/+ liver metabolism, marrow toxicity, colon target
26
Q

assay potential chemo drug: cell survival

A
  • liver chamber empty and full is the same output
  • no liver cells with drug
  • and liver cells and drug

*impact on tumor cells

27
Q

your interpretation of toxicity? any negative effect on bone marrow cells? regarding effectiveness (reducing tumor cell number

A
  • many cancer chemotherapy drugs decrease WBC counts
  • all bone marrow cells survived with and without the liver but with parent compound or predicted metabolite (drug)
  • the drug has an increased impact on colon cancer cells in presence of liver because fewer live tumor cells (metabolize to a more active form)

*would not have seen without a complex model system (whole physiology)