exam 1 Flashcards
- What aspects are distinct in biopharmaceuticals vs. drugs?
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- What are the advantages of recombinant DNA technology over traditional methods?
- Overcomes the problem of source availability
- Overcomes problems of product safety
- Provides an alternative to direct extraction from inappropriate/dangerous source material
- Facilitates the generation of engineered therapeutic proteins displaying some clinical
advantages over the native protein product
- What are some of the hurdles to overcome for cell therapy manufacturing?
- Scaling up for adherent cell cultures
- Purification methods (magnetic bead separation contamination
- Viral gene transfer
- What are the drivers behind the rapid growth in AI health applications?
- Breakthroughs in methods (e.g., deep neural networks, reinforcement learning,
Generative adversarial networks, Variational autoencoders, etc.) and causal inference
approaches (e.g., structural causal models and causal Bayesian networks) - Large datasets (e.g., administrative data, EHRs, registries, etc.)
- Diverse and multimodal datasets (e.g., DHTs, genomic, laboratory, imaging, etc.)
- Improvements in data standards (e.g., ICD-10, LOINC, NDCs, UMLS, FHIR/HL7, OHDSI,
etc.) - Improved data interoperability and healthcare data exchange
- Increased computing power
- Advancements in data privacy persevering approaches
- A study on reproducibility showed that machine learning for health underperformed in all areas of replicability when compared to Computer vision, Natural language processing, and General Machine Learning: why is this the case?
Due to the sensitive nature of patient data, reproducibility can be limited for health applications of machine learning.
- Give some examples of where bias arises in AI for health applications and why is it particularly detrimental?
- Unfair sampling can skew the model
- Human bias can interfere with data selection/weighting
It is detrimental in the case of an AI application that could potentially affect millions of people
with a biased evaluation
- In class we discussed how adversarial examples are designed to cause a machine learning algorithm to make a mistake, what is the purpose behind this?
It is used to demonstrate the weaknesses in an algorithm, particularly in the context of ML
applications that are intended to operate without human supervision. (EKG example)
- How can genomics, transcriptomics, proteomics, and metabolomics all contribute to discovery of new therapeutics?
Genomics is key in the characterization of inheritable disorders which allows direct insights not only into disease and disease susceptibility, but also increasingly in the study of complex diseases.
The study of RNA expression—includes not only the evaluation of mRNA, but also other RNA types, including RNAs involved in posttranscriptional modification and regulatory mechanisms.
While the study of the human genome is the study of a static system, which is not subject to
fluctuations of quantity, the field of transcriptomics reflects a discipline that seeks to measure fluctuations in levels of RNAs over /me and in response to various perturbations.
Proteins can not only vary in their abundance (e.g., as described for HER2), but they can also be modified (postranslational modifications), a process that can be specific to certain diseases or other influences, and may alter the function of the protein. Therefore elucidating such changes
can lead to the identification of key targets that if modified (e.g., blocked by an inhibitory
molecule) may have a direct therapeutic effect or may be indirectly indicative of a therapeutic
effect.
The metabolome is a direct functional measure of the activity of the proteome and can be
highly variable according to the environment it is derived from (e.g., the metabolome of the
blood is significantly different than the metabolome of a liver cell
- Why is it important to have an independent test set for an ML model
If a machine learning model is modified based upon the results of a test set, the modified
algorithm cannot be verified with the same test set as it is no longer truly independent. This helps to ensure valid results
- Describe 3 different contributing factors to aging
- What is cellular senescence?
Refers to a state of stable cell cycle arrest in which proliferating cells become resistant to
growth-promoting stimuli, typically in response to DNA damage
- What are some causes of cell senescence
DNA damage
Telomere shortening
Dysregulated inflammation
Alteration of epigenetic modifications
Metabolic imbalance
Oncogene activation
Mitochondrial dysfunction
Production of reactive oxygen species
Accumulation of excess metals
- Describe how senescent cells can cause/contribute to disease.
Once senescent cell burden exceeds a threshold, self-amplifying paracrine and endocrine spread of senescence through the SASP outpaces clearance of senescent cells by the immune system. Additionally, increased abundance of SASP factors may impede immune system function, further amplifying accumulation of senescent cells and subsequently accelerate other
fundamental aging mechanisms, and contribute to age-related disease
- Describe the detrimental cellular senescent feedback loop
Cellular senescence is induced following exposure to an initial stress. The resulting senescent cells produce a SASP that can potentiate further senescent cell accumulation and impair clearance by affecting immune cells. In turn, the SASP can be amplified, eliciting an environment of chronic inflammation and additional senescence-inducing stressors that drive a feed-forward
cycle of senescent cell accumulation
Cellular sensecent are induced/activated by initial stress. Senescent cells produce a SASP that potentiates the accumulation of senscent cells and overwhelms the immune response. This leads to the amplication of SASP resulting into an environment of chronic stress and inflammation. This process then becomes a feed forward loop
- What is the difference between senolytics and senomorphics?
Senolytics target the molecular pathways that are dysregulated in senescent cells,
senomorphics try to attenuate the various inflammatory signaling molecules that are secreted.
