Daclizumab

Hybridoma technology: is it still useful?

The isolation of single monoclonal antibodies (mAbs) against a given antigen was only possible with the introduction of the hybridoma technology, which is based on the fusion of specific B lymphocytes with myeloma cells. Since then, several mAbs were described for therapeutic, diagnostic, and research purposes. Despite being an old technique with low complexity, hybridoma-based strategies have limitations that include the low efficiency on B lymphocyte-myeloma cell fusion step, and the need to use experimental animals. In face of that, several methods have been developed to improve mAb generation, ranging from changes in hybridoma technique to the advent of completely new technologies, such as the antibody phage display and the single B cell antibody ones. In this review, we discuss the hybridoma technology along with emerging mAb isolation approaches, taking into account their advantages and limitations. Finally, we explore the usefulness of the hybridoma technology nowadays.

•

Hybridoma technology is the most popular technique to obtain monoclonal antibodies.

•

Hybridoma technology variants include B cell and stereospecific targeting protocols.

•

Phage display and single B cell methods are hybridoma technology alternatives.

Current and Emerging Targeted Therapies for Acute Graft-Versus-Host Disease

Acute graft-versus-host disease (GVHD), the major complication after allogeneic hematopoietic cell transplant (HCT), develops in approximately 50% of patients. The primary treatment is high-dose systemic steroids, but treatment failure is common, and steroid-refractory (SR) GVHD is the leading cause of non-relapse mortality after allogeneic HCT. Ruxolitinib became the first treatment for SR GVHD to obtain US Food and Drug Administration approval, and other new treatments are actively being studied. We searched the literature using the PubMed database and clinical trials using ClinicalTrials.gov to identify the most promising new treatments for GVHD. In this review, we categorize potential new treatments for GVHD by their mechanism of action (e.g., antibodies that deplete T cells or prevent their trafficking to target tissues, proteasome inhibitors, tyrosine kinase inhibitors, and other agents) and summarize the results from clinical trials.

A computational approach based on the colored Petri net formalism for studying multiple sclerosis

Background

Multiple Sclerosis (MS) is an immune-mediated inflammatory disease of the Central Nervous System (CNS) which damages the myelin sheath enveloping nerve cells thus causing severe physical disability in patients. Relapsing Remitting Multiple Sclerosis (RRMS) is one of the most common form of MS in adults and is characterized by a series of neurologic symptoms, followed by periods of remission. Recently, many treatments were proposed and studied to contrast the RRMS progression. Among these drugs, daclizumab (commercial name Zinbryta), an antibody tailored against the Interleukin-2 receptor of T cells, exhibited promising results, but its efficacy was accompanied by an increased frequency of serious adverse events. Manifested side effects consisted of infections, encephalitis, and liver damages. Therefore daclizumab has been withdrawn from the market worldwide. Another interesting case of RRMS regards its progression in pregnant women where a smaller incidence of relapses until the delivery has been observed.

Results

In this paper we propose a new methodology for studying RRMS, which we implemented in GreatSPN, a state-of-the-art open-source suite for modelling and analyzing complex systems through the Petri Net (PN) formalism. This methodology exploits: (a) an extended Colored PN formalism to provide a compact graphical description of the system and to automatically derive a set of ODEs encoding the system dynamics and (b) the Latin Hypercube Sampling with PRCC index to calibrate ODE parameters for reproducing the real behaviours in healthy and MS subjects.To show the effectiveness of such methodology a model of RRMS has been constructed and studied. Two different scenarios of RRMS were thus considered. In the former scenario the effect of the daclizumab administration is investigated, while in the latter one RRMS was studied in pregnant women.

Conclusions

We propose a new computational methodology to study RRMS disease. Moreover, we show that model generated and calibrated according to this methodology is able to reproduce the expected behaviours.