Hot Topics in Drug Development [April 2016]
type of data should be shared,
ethods for sharing data, what groups
should have access to data, and future
knowledge and infrastructure needs.
APPLICATION OF BIOMARKERS
Autoantibodies in CNS trauma
and neuropsychiatric disorders:
a new generation of biomarkers.
Kobeissy F, Moshourab RA. In:
Kobeissy FH (ed). Brain
Rehabilitation Aspects. Boca Raton
FL: CRC Press/Taylor & Francis;
2015. Chapter 29.
Summary: In this book chapter,
the authors discuss the genesis and
implications of autoantibodies in
neurotrauma—focusing on the area
of spinal cord injury and shedding
light on recent application in
traumatic brain injury. In addition,
the authors evaluate the potential
pathogenic mechanistic role of
autoantibodies in the areas of autism
spectrum disorder and neurotoxicity,
as this may reflect on the neural
injury observed in brain trauma.
Novel agents for the treatment
of childhood acute leukemia.
Annesley CE, Brown P. Ther Adv
Hematol. 2015;6(2):61–79. doi:
Summary: Here the authors
detail the rationale and
implementation of recent and
specifically targeted therapies in
acute pediatric leukemia. They
discuss inhibition of critical cell
signaling pathways [BCR-ABL, FMS-
like tyrosine kinase 3 (FLT3),
mammalian target of rapamycin
(mTOR), and Janus-associated
kinase (JAK)], proteasome
inhibition, inhibition of epigenetic
regulators of gene expression [DNA
inhibitors, histone deacetylase
HDAC) inhibitors, and disruptor of
telomeric signaling-1 (DOT1L)
inhibitors], monoclonal antibodies
and immunoconjugated toxins,
bispecific T-cell engaging (BiTE)
antibodies, and chimeric antigen
receptor-modified (CAR) T cells.
Novel methodologies for
biomarker discovery in
Hoefer IE, Steffens S, Ala-Korpela M,
et al. Eur Heart J. 2015 Oct
10.1093/eurheartj/ehv236. Epub 2015
Summary: In this position paper,
the authors provide a summary of
current vascular biomarkers other
than the traditional risk factors and
specifically focus on the emerging
-omics technologies. The authors
introduce the definition of
biomarkers and the identification
and use of classical biomarkers, as
well as discuss the limitations of
current biomarkers such as high
sensitivity C-reactive protein
(hsCRP) or N-terminal pro-brain
natriuretic peptide (NT-proBNP).
"DEEP LEARNING" AND DRUG
Impact of the digital revolution
on the future of pharmaceutical
Leuenberger H, Leuenberger MN.
Eur J Pharm Sci. 2016 Feb 11. pii:
ahead of print].
Summary: Researchers describe
a new software platform called F-
CAD (Formulation-Computer Aided
Design) of CINCAP, which can be
used to develop and test in silico
capsule and tablet formulations. The
software is based on a cellular
automaton process that mimics the
issolution profile of the capsule or
tablet formulation. The authors go
into great detail describing the
software and its applications in drug
development. The authors suggest
that in the future, it may be possible
to rent at low costs F-CAD as an IT
(Information Technology) platform
based on a cloud computing solution.
Applications of deep learning in
Mamoshina P, Vieira A, Putin E,
Zhavoronkov A. Mol Pharm. 2016
Mar 29 [Epub ahead of print].
Summary: The authors describe
deep neural networks (DNNs) as
efficient algorithms based on the use
of compositional layers of neurons.
The authors discuss key features of
deep learning that may give this
approach an edge over other
machine learning methods. They
then discuss limitations and review a
number of applications of deep
learning in biomedical studies
demonstrating proof of concept and
Gene expression inference
with deep learning.
Chen Y, Li Y, Narayan R, et
al. Bioinformatics. 2016
Feb 11. pii: btw074.
[Epub ahead of print].
method (abbreviated as
D-GEX) to infer the
expression of target genes
from the expression of
landmark genes. The
authors used the
dataset, consisting of 111K
expression profiles, to train