High-throughput screening for best clone manufacturing using scale-down models

The timelines for cell line development and early-stage process development are decreasing, but simultaneously there has been an increase in the amount of associated data. New methods in molecular and cell biology, new analytical methods, including the application of Process Analytical Techniques (PATs) and other methods to assess product quality early on, as well as new trends in process miniaturization and automation, increase the throughput in cell line and early-stage process development and the amount of data needed to be analyzed and reviewed. Thus, data structuring and curation represents a serious bottleneck to proper data analysis and valid decision making. We have designed a highly integrated data management and workflow system, which supports automated clone and manufacturing process development workflows, and provides the foundation to increase throughput in cell line and process development. The system is designed to continuously capture, in a highly structured manner, the heterogeneous data during the course of process development campaigns. It supports the whole process from expression, construct generation via transfection, cell seeding, selection, passaging, and cryo-conservation to cell culture and product quality analytics. This includes repeated passaging for clone stability assessments as well as (micro-) bioreactor runs for clone selection and process optimization. It can handle molecule, cell line, sample and process information as well as analytical test results. The system tracks the full history of all clones - from initial transfection all the way to their master cell banking and beyond - and provides lineage information for all samples handled during a campaign. Here, we present concrete use cases to demonstrate how the platform supports miniaturized screening approaches in scale-down models such as microtiter plate and micro-bioreactor based clone and process screening by capturing, processing, aggregating, and visualizing online and offline data and integrating them with product quality and molecule data to enable holistic process development for any type of biologics molecules (IgGs, novel antibody formats, novel scaffold, fusion proteins, enzymes, etc.)

A novel platform for high throughput cell line screening & development

The provision of stably expressing, high-yield mammalian cell lines is a key step in bioprocess development. Recent progress in clone screening automation, and the increased use of mini-bioreactors, such as ambr®, have resulted in higher experimental throughput and a significant increase in data that needs to be handled and interpreted. Co-developed in close collaboration with leading biopharmaceutical companies, we have implemented a dedicated cell line development platform for fully automating the clone line selection and assessment process to increase process efficiency and quality. The new platform supports the entire cell line development workflow including seeding, selection, incubation, passaging, analyzing, and cryo-conservation of cells. The system tracks the full history of all clones - from initial transfection all the way to their evaluation in bioreactor runs - and combines this information with product quality and analytics data. As a fully integrated platform, it directly integrates with all instruments, such as pipetting robots, colony pickers, and bioanalyzers. The platform can be applied to both antibodies (IgGs, novel formats) as well as therapeutic proteins (e.g. engineered FVIII variants, fusion proteins). Here, we present concrete use cases to demonstrate how the platform streamlines the generation and assessment of mammalian production cell lines, shortening typical cell line development campaigns and significantly reducin

A Markov Chain Algorithm for determining Crossing Times through nested Graphs

According to the by now established theory developed in order to define a Laplacian or ― equivalently ― a Brownian motion on a nested fractal, one has to solve certain renormalization problems. In this paper, we present a Markov chain algorithm solving the problem for certain classes of simple fractals $K$ provided that there exists a unique Brownian motion and hence, a unique Laplacian on $K$

Exact Computation and Approximation of Stochastic and Analytic Parameters of Generalized Sierpinski Gaskets

The interplay of fractal geometry, analysis and stochastics on the one-parameter sequence of self-similar generalized Sierpinski gaskets is studied. An improved algorithm for the exact computation of mean crossing times through the generating graphs SG(m) of generalized Sierpinski gaskets sg(m) for m up to 37 is presented and numerical approximations up to m = 100 are shown. Moreover, an alternative method for the approximation of the mean crossing times, the walk and the spectral dimensions of these fractal sets based on quasi-random so-called rotor walks is developed, confidence bounds are calculated and numerical results are shown and compared with exact values (if available) and with known asymptotic formula

A randomized, phase III trial of capecitabine plus bevacizumab (Cape-Bev) versus capecitabine plus irinotecan plus bevacizumab (CAPIRI-Bev) in first-line treatment of metastatic colorectal cancer: The AIO KRK 0110 Trial/ML22011 Trial

<p>Abstract</p> <p>Background</p> <p>Several randomized trials have indicated that combination chemotherapy applied in metastatic colorectal cancer (mCRC) does not significantly improve overall survival when compared to the sequential use of cytotoxic agents (CAIRO, MRC Focus, FFCD 2000-05). The present study investigates the question whether this statement holds true also for bevacizumab-based first-line treatment including escalation- and de-escalation strategies.</p> <p>Methods/Design</p> <p>The AIO KRK 0110/ML22011 trial is a two-arm, multicenter, open-label randomized phase III trial comparing the efficacy and safety of capecitabine plus bevacizumab (Cape-Bev) versus capecitabine plus irinotecan plus bevacizumab (CAPIRI-Bev) in the first-line treatment of metastatic colorectal cancer. Patients with unresectable metastatic colorectal cancer, Eastern Cooperative Oncology Group (ECOG) performance status 0-1, will be assigned in a 1:1 ratio to receive either capecitabine 1250 mg/m²bid for 14d (d1-14) plus bevacizumab 7.5 mg/kg (d1) q3w (Arm A) or capecitabine 800 mg/m²BID for 14d (d1-14), irinotecan 200 mg/m²(d1) and bevacizumab 7.5 mg/kg (d1) q3w (Arm B). Patients included into this trial are required to consent to the analysis of tumour tissue and blood for translational investigations. In Arm A, treatment escalation from Cape-Bev to CAPIRI-Bev is recommended in case of progressive disease (PD). In Arm B, de-escalation from CAPIRI-Bev to Cape-Bev is possible after 6 months of treatment or in case of irinotecan-associated toxicity. Re-escalation to CAPIRI-Bev after PD is possible. The primary endpoint is time to failure of strategy (TFS). Secondary endpoints are overall response rate (ORR), overall survival, progression-free survival, safety and quality of life.</p> <p>Conclusion</p> <p>The AIO KRK 0110 trial is designed for patients with disseminated, but asymptomatic mCRC who are not potential candidates for surgical resection of metastasis. Two bevacizumab-based strategies are compared: one starting as single-agent chemotherapy (Cape-Bev) allowing escalation to CAPIRI-Bev and another starting with combination chemotherapy (CAPIRI-Bev) and allowing de-escalation to Cape-Bev and subsequent re-escalation if necessary.</p> <p>Trial Registration</p> <p>ClinicalTrials.gov Identifier <a href="http://www.clinicaltrials.gov/ct2/show/NCT01249638">NCT01249638</a></p> <p>EudraCT-No.: 2009-013099-38</p

Exact computation and approximation of stochastic and analytic parameters of generalized Sierpinski gaskets

The interplay of fractal geometry, analysis and stochastics on the oneparameter sequence of self-similar generalized Sierpinski gaskets is studied. An improved algorithm for the exact computation of mean crossing times through the generating graphs SG(m) of generalized Sierpinski gaskets sg(m) for m up to 37 is presented and numerical approximations up to m = 100 are shown. Moreover, an alternative method for the approximation of the mean crossing times, the walk and the spectral dimensions of these fractal sets based on quasi-random so-called rotor walks is developed, confidence bounds are calculated and numerical results are shown and compared with exact values (if available) and with known asymptotic formulas

A Markov Chain Algorithm for determining Crossing Times through nested Graphs

According to the by now established theory developed in order to define a Laplacian or ― equivalently ― a Brownian motion on a nested fractal, one has to solve certain renormalization problems. In this paper, we present a Markov chain algorithm solving the problem for certain classes of simple fractals $K$ provided that there exists a unique Brownian motion and hence, a unique Laplacian on $K$

Sequencing the 500-kb GC-rich Symbiotic Replicon of <i>Rhizobium</i> sp. NGR234 Using Dye Terminators and a Thermostable "Sequenase": a beginning

Genomes of the soil-borne nitrogen-fixing symbionts of legumes [Azo(Brady)Rhizobium species] typically have GC contents of 59-65 mol%. As a consequence, compressions (up to 400 per cosmid) are common using automated dye primer shotgun sequencing methods. To overcome this difficulty, we have exclusively applied dye terminators in combination with a thermostable "sequenase" for shotgun sequencing GC-rich cosmids from pNGR234a, the 500-kbp symbiotic replicon of Rhizobium sp. NGR234. A thermostable sequenase incorporates dye terminators into DNA more efficiently than Taq DNA polymerase, thus reducing the concentrations needed (20- to 250-fold). Unincorporated dye terminators can simply be removed by ethanol precipitation. Here, we present data of pXB296, one of 23 overlapping cosmids representing pNGR234a. We demonstrate that the greatly reduced number of compressions results in a much faster assembly of cosmid sequence data by comparing assembly of the shotgun data from pXB296 and the data from another pNGR234a cosmid (pXB110) sequenced using dye primer methods. Within the 34,010-bp sequence from pXB296, 28 coding regions were predicted. All of them showed significant homologies to known proteins, including oligopeptide permeases, an essential cluster for nitrogen fixation, and the C4-dicarboxylate transporter DctA